Not-For-All-Audiences

abliterated

heretic

uncensor

hermes-lineage

Model card Files Files and versions

xet

Community

Instructions to use oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Use Docker

docker model run hf.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

LM Studio
Jan

vLLM

How to use oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Ollama
How to use oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama with Ollama:
```
ollama run hf.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M
```
Unsloth Desktop

How to use oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama with Docker Model Runner:
```
docker model run hf.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M
```

Lemonade

How to use oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

oktayd commited on 24 days ago

Commit

c9aaaa2

verified ·

1 Parent(s): 48368ea

Add approved Istanbul banner and shorten dataset description

Browse files

Files changed (5) hide show

.gitattributes +1 -0
DATASETS.md +175 -177
README.md +159 -157
SHA256SUMS +3 -2
assets/qwen3.6-35b-v2-banner.png +3 -0

.gitattributes CHANGED Viewed

@@ -49,3 +49,4 @@ Qwen3.6-35B-v2-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
 Qwen3.6-35B-v2-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
 Qwen3.6-35B-v2-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
 mmproj-Qwen3.6-35B-v2-F16.gguf filter=lfs diff=lfs merge=lfs -text

 Qwen3.6-35B-v2-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
 Qwen3.6-35B-v2-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
 mmproj-Qwen3.6-35B-v2-F16.gguf filter=lfs diff=lfs merge=lfs -text
+assets/qwen3.6-35b-v2-banner.png filter=lfs diff=lfs merge=lfs -text

DATASETS.md CHANGED Viewed

@@ -1,177 +1,175 @@
-# Dataset sources
-This list attributes the sources recorded for the three training runs (6,000 / 12,000 / 16,000 uses). A record use is not necessarily a unique image or example. Selected samples were used, not entire upstream datasets. Follow each source page for its description and licensing; those licenses are not replaced by the model license.
-## Private, manually prepared packages
-| Package | Recorded uses | Source |
-|---|---:|---|
-| Broad adult learning | 3,070 | Private curation; not distributed |
-| Synthetic 3D model adult learning | 133 | Private synthetic multi-view groups; not distributed |
-The Chinese-caption contribution is a small sample (13 recorded uses across two source adapters). No private images, identities, captions or paths are included here.
-## Public sources in the local training pool
-Counts are grouped by source adapter, so multiple rows can point to the same upstream dataset.
-| Source / adapter | Recorded uses | Source page |
-|---|---:|---|
-| `2796gauravc/agentic-search-data` | 176 | [2796gauravc/agentic-search-data](https://huggingface.co/datasets/2796gauravc/agentic-search-data) |
-| `A02_CHINESE_DIRECT_FRESH` | 6 | [Richarddzz/NSFW-Chinese-Adult-Image-Caption](https://huggingface.co/datasets/Richarddzz/NSFW-Chinese-Adult-Image-Caption) |
-| `A03_HDR` | 17 | [thisnick/nsfw-video-still-caption-grid-only](https://huggingface.co/datasets/thisnick/nsfw-video-still-caption-grid-only) |
-| `A03_VIDEO_STILLS` | 51 | [thisnick/nsfw-video-still-caption-grid-only](https://huggingface.co/datasets/thisnick/nsfw-video-still-caption-grid-only) |
-| `AfterQuery/FinanceQA` | 22 | [AfterQuery/FinanceQA](https://huggingface.co/datasets/AfterQuery/FinanceQA) |
-| `ahhany/constructionQAs` | 67 | [ahhany/constructionQAs](https://huggingface.co/datasets/ahhany/constructionQAs) |
-| `Ailiance-fr/mascarade-stm32-dataset` | 140 | [Ailiance-fr/mascarade-stm32-dataset](https://huggingface.co/datasets/Ailiance-fr/mascarade-stm32-dataset) |
-| `Alogotron/game-theory-business-strategy` | 1 | [Alogotron/game-theory-business-strategy](https://huggingface.co/datasets/Alogotron/game-theory-business-strategy) |
-| `AmazonScience/migration-bench-java-full` | 252 | [AmazonScience/migration-bench-java-full](https://huggingface.co/datasets/AmazonScience/migration-bench-java-full) |
-| `Atomic-Germ/Pygame-data` | 147 | [Atomic-Germ/Pygame-data](https://huggingface.co/datasets/Atomic-Germ/Pygame-data) |
-| `B01_VQARAD_DIRECT` | 40 | [abhay2812/vqa-rad](https://huggingface.co/datasets/abhay2812/vqa-rad) |
-| `B02_BODY_MEASUREMENTS_UNIQUEDATA_ADULT_DIRECT_0019` | 1 | [UniqueData/body-measurements-dataset](https://huggingface.co/datasets/UniqueData/body-measurements-dataset) |
-| `B02_FASHION_DE` | 52 | [jinaai/fashion-captions-de](https://huggingface.co/datasets/jinaai/fashion-captions-de) |
-| `B02_HUMANPOSE_DENSEPOSE_SMALLDATA_DIRECT_0067` | 5 | [jschoormans/humanpose_densepose](https://huggingface.co/datasets/jschoormans/humanpose_densepose) |
-| `B03_CAULDRON_VISUAL7W` | 31 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B03_CAULDRON_VQAV2` | 32 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B04_CAULDRON_LNARR` | 34 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B04_CAULDRON_TEXTCAPS` | 29 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B05_CAPTCHA_HANDOFF_VENUSBENCH_0219` | 60 | [inclusionAI/VenusBench-CAPTCHA](https://huggingface.co/datasets/inclusionAI/VenusBench-CAPTCHA) |
-| `B05_ORCHARD_GUI` | 100 | [microsoft/Orchard](https://huggingface.co/datasets/microsoft/Orchard) |
-| `B05_UNIGUI1` | 15 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B05_UNIGUI2` | 15 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B06_CHARTQA` | 16 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B06_DOCVQA` | 18 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B06_GEOGUESSR_COUNTRY_CAPPED_0116` | 7 | [fren-gor/geoguessr-locations](https://huggingface.co/datasets/fren-gor/geoguessr-locations) |
-| `B06_INFOVQA` | 19 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B06_MAPQA` | 3 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B06_MEMES_HF_CAPPED_DEDUP` | 10 | [sin3142/memes-1500](https://huggingface.co/datasets/sin3142/memes-1500) |
-| `B06_OCRVQA` | 15 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B06_RENDERED` | 7 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B06_TEXTVQA` | 15 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B07_AKIS` | 13 | [OttomanNLP/Akis-Ottoman-Dataset](https://huggingface.co/datasets/OttomanNLP/Akis-Ottoman-Dataset) |
-| `B07_CHURRO` | 15 | [OttomanNLP/CHURRO-Ottoman-Turkish-Subset](https://huggingface.co/datasets/OttomanNLP/CHURRO-Ottoman-Turkish-Subset) |
-| `B07_PERSIAN` | 8 | [MR3z4/persian-handwriting-ocr](https://huggingface.co/datasets/MR3z4/persian-handwriting-ocr) |
-| `B08_CAULDRON_AI2D` | 21 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B08_OPEN_SCHEMATICS` | 82 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B09_3DCODE_DIRECT_CAPPED_0212` | 16 | [YipengGao/3DCode](https://huggingface.co/datasets/YipengGao/3DCode) |
-| `B09_CAP3D_ABO` | 17 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B10_AI2D` | 26 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B10_FIGUREQA` | 18 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B10_PLOTQA` | 12 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B10_SCIENCEQA` | 14 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B11_OPENWEBRL_REUSE` | 32 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B11_ORCHARD_SEQUENCE` | 3 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B12_CAULDRON_AOKVQA` | 19 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B12_CAULDRON_CLEVR` | 8 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B12_CAULDRON_COCOQA` | 18 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B12_CAULDRON_NLVR2` | 12 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
-| `B12_CAULDRON_OKVQA` | 11 | Local adapter; exact upstream URL not recoverable from the retained source lock |
-| `B13_FACE_EXPRESSION_MIT_DIRECT_0392` | 4 | [Prasanna18/Human-Face_Images_for_Emotion_Recognition](https://huggingface.co/datasets/Prasanna18/Human-Face_Images_for_Emotion_Recognition) |
-| `Bakanayatsu/nsfw-image-public` | 1 | [Bakanayatsu/nsfw-image-public](https://huggingface.co/datasets/Bakanayatsu/nsfw-image-public) |
-| `bernabepuente/backend-api-instruction-dataset` | 132 | [bernabepuente/backend-api-instruction-dataset](https://huggingface.co/datasets/bernabepuente/backend-api-instruction-dataset) |
-| `BYC-Sophie/samsum-chatgpt-summary` | 46 | [BYC-Sophie/samsum-chatgpt-summary](https://huggingface.co/datasets/BYC-Sophie/samsum-chatgpt-summary) |
-| `CATIE-AQ/XMRec_reviews_fr_Electronics` | 972 | [CATIE-AQ/XMRec_reviews_fr_Electronics](https://huggingface.co/datasets/CATIE-AQ/XMRec_reviews_fr_Electronics) |
-| `Chat-Error/anime_pretraining_2` | 96 | [Chat-Error/anime_pretraining_2](https://huggingface.co/datasets/Chat-Error/anime_pretraining_2) |
-| `Christine-HiAiPerf/canadian-tax-law-qa` | 948 | [Christine-HiAiPerf/canadian-tax-law-qa](https://huggingface.co/datasets/Christine-HiAiPerf/canadian-tax-law-qa) |
-| `ChuckMcSneed/various_RP_system_prompts` | 87 | [ChuckMcSneed/various_RP_system_prompts](https://huggingface.co/datasets/ChuckMcSneed/various_RP_system_prompts) |
-| `ClarusC64/legal-advice-email-risk-option-instruction-coherence-v0.1` | 3 | [ClarusC64/legal-advice-email-risk-option-instruction-coherence-v0.1](https://huggingface.co/datasets/ClarusC64/legal-advice-email-risk-option-instruction-coherence-v0.1) |
-| `ClarusC64/legal-counsel-brief-fact-issue-instruction-coherence-risk-v0.1` | 4 | [ClarusC64/legal-counsel-brief-fact-issue-instruction-coherence-risk-v0.1](https://huggingface.co/datasets/ClarusC64/legal-counsel-brief-fact-issue-instruction-coherence-risk-v0.1) |
-| `ClarusC64/network-security-route-hijack-coherence-risk-v0.1` | 3 | [ClarusC64/network-security-route-hijack-coherence-risk-v0.1](https://huggingface.co/datasets/ClarusC64/network-security-route-hijack-coherence-risk-v0.1) |
-| `CollateralAnalytics/kgp-synthetic-customer-behavior-segments` | 1 | [CollateralAnalytics/kgp-synthetic-customer-behavior-segments](https://huggingface.co/datasets/CollateralAnalytics/kgp-synthetic-customer-behavior-segments) |
-| `community-datasets/europa_eac_tm` | 288 | [community-datasets/europa_eac_tm](https://huggingface.co/datasets/community-datasets/europa_eac_tm) |
-| `contralabs/creative-ad-design-dataset` | 4 | [contralabs/creative-ad-design-dataset](https://huggingface.co/datasets/contralabs/creative-ad-design-dataset) |
-| `cowWhySo/pentest-redteam-steering` | 151 | [cowWhySo/pentest-redteam-steering](https://huggingface.co/datasets/cowWhySo/pentest-redteam-steering) |
-| `crazycog/linux-sysadmin-qa-askhole` | 78 | [crazycog/linux-sysadmin-qa-askhole](https://huggingface.co/datasets/crazycog/linux-sysadmin-qa-askhole) |
-| `crazycog/linux-sysadmin-qa-askhole-v1` | 782 | [crazycog/linux-sysadmin-qa-askhole-v1](https://huggingface.co/datasets/crazycog/linux-sysadmin-qa-askhole-v1) |
-| `CyberNative/Code_Vulnerability_Security_DPO` | 486 | [CyberNative/Code_Vulnerability_Security_DPO](https://huggingface.co/datasets/CyberNative/Code_Vulnerability_Security_DPO) |
-| `David-Chew-HL/Tech-Stocks-News` | 627 | [David-Chew-HL/Tech-Stocks-News](https://huggingface.co/datasets/David-Chew-HL/Tech-Stocks-News) |
-| `Draeg82/uk-gdpr-small-business-qa` | 242 | [Draeg82/uk-gdpr-small-business-qa](https://huggingface.co/datasets/Draeg82/uk-gdpr-small-business-qa) |
-| `electricsheepafrica/africa-south-sudan-global-subnational-population-statistics-f60bb180` | 71 | [electricsheepafrica/africa-south-sudan-global-subnational-population-statistics-f60bb180](https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-global-subnational-population-statistics-f60bb180) |
-| `electricsheepafrica/africa-synth-retail-and-ecommerce-supply-chain-logistics-data-nigeria` | 677 | [electricsheepafrica/africa-synth-retail-and-ecommerce-supply-chain-logistics-data-nigeria](https://huggingface.co/datasets/electricsheepafrica/africa-synth-retail-and-ecommerce-supply-chain-logistics-data-nigeria) |
-| `electricsheepafrica/africa-wearable-device-security` | 1,662 | [electricsheepafrica/africa-wearable-device-security](https://huggingface.co/datasets/electricsheepafrica/africa-wearable-device-security) |
-| `electricsheepafrica/africa-worldbank-wbl-supportive-framework-entrepreneurship-there-are-government-led-programs-sup` | 3 | [electricsheepafrica/africa-worldbank-wbl-supportive-framework-entrepreneurship-there-are-government-led-programs-sup](https://huggingface.co/datasets/electricsheepafrica/africa-worldbank-wbl-supportive-framework-entrepreneurship-there-are-government-led-programs-sup) |
-| `electricsheepafrica/nigerian_transport_and_logistics_environmental_impact` | 684 | [electricsheepafrica/nigerian_transport_and_logistics_environmental_impact](https://huggingface.co/datasets/electricsheepafrica/nigerian_transport_and_logistics_environmental_impact) |
-| `eniomecaj/embedded-systems-qa` | 138 | [eniomecaj/embedded-systems-qa](https://huggingface.co/datasets/eniomecaj/embedded-systems-qa) |
-| `facebook/asset` | 600 | [facebook/asset](https://huggingface.co/datasets/facebook/asset) |
-| `Falah/interior_design_prompts_SDXL` | 6 | [Falah/interior_design_prompts_SDXL](https://huggingface.co/datasets/Falah/interior_design_prompts_SDXL) |
-| `Finance-Agentic-AI/Portfolio-Rebalance` | 34 | [Finance-Agentic-AI/Portfolio-Rebalance](https://huggingface.co/datasets/Finance-Agentic-AI/Portfolio-Rebalance) |
-| `gjyotk/Menstrual-Health-Awareness-Dataset` | 105 | [gjyotk/Menstrual-Health-Awareness-Dataset](https://huggingface.co/datasets/gjyotk/Menstrual-Health-Awareness-Dataset) |
-| `google-research-datasets/aquamuse` | 175 | [google-research-datasets/aquamuse](https://huggingface.co/datasets/google-research-datasets/aquamuse) |
-| `google/mobile-actions` | 278 | [google/mobile-actions](https://huggingface.co/datasets/google/mobile-actions) |
-| `Gopher-Lab/huberman_lab_The_Science_of_Sexual_Development` | 1 | [Gopher-Lab/huberman_lab_The_Science_of_Sexual_Development](https://huggingface.co/datasets/Gopher-Lab/huberman_lab_The_Science_of_Sexual_Development) |
-| `greghavens/gpt-5.6-sol-coding-and-debugging-traces` | 49 | [greghavens/gpt-5.6-sol-coding-and-debugging-traces](https://huggingface.co/datasets/greghavens/gpt-5.6-sol-coding-and-debugging-traces) |
-| `gretelai/synthetic_pii_finance_multilingual` | 371 | [gretelai/synthetic_pii_finance_multilingual](https://huggingface.co/datasets/gretelai/synthetic_pii_finance_multilingual) |
-| `Gryphe/Opus-WritingPrompts` | 51 | [Gryphe/Opus-WritingPrompts](https://huggingface.co/datasets/Gryphe/Opus-WritingPrompts) |
-| `GyeongjuLee/instruction-tuning_EMH-emotional-reactions` | 20 | [GyeongjuLee/instruction-tuning_EMH-emotional-reactions](https://huggingface.co/datasets/GyeongjuLee/instruction-tuning_EMH-emotional-reactions) |
-| `Imrankhanjoya/ecommerce-onionpose` | 305 | [Imrankhanjoya/ecommerce-onionpose](https://huggingface.co/datasets/Imrankhanjoya/ecommerce-onionpose) |
-| `income/scidocs-top-20-gen-queries` | 889 | [income/scidocs-top-20-gen-queries](https://huggingface.co/datasets/income/scidocs-top-20-gen-queries) |
-| `infinite-dataset-hub/OvarianUltrasoundFeatureExtraction` | 3 | [infinite-dataset-hub/OvarianUltrasoundFeatureExtraction](https://huggingface.co/datasets/infinite-dataset-hub/OvarianUltrasoundFeatureExtraction) |
-| `introvoyz041/farmbot-arduino-firmware` | 1 | [introvoyz041/farmbot-arduino-firmware](https://huggingface.co/datasets/introvoyz041/farmbot-arduino-firmware) |
-| `ismailtasdelen/ethereum-smart-contract-security-qa` | 64 | [ismailtasdelen/ethereum-smart-contract-security-qa](https://huggingface.co/datasets/ismailtasdelen/ethereum-smart-contract-security-qa) |
-| `jjmachan/NSFW-questions-inter-cleaned_df` | 19 | [jjmachan/NSFW-questions-inter-cleaned_df](https://huggingface.co/datasets/jjmachan/NSFW-questions-inter-cleaned_df) |
-| `johndoe1100100101/nsfw_chat` | 3 | [johndoe1100100101/nsfw_chat](https://huggingface.co/datasets/johndoe1100100101/nsfw_chat) |
-| `Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample` | 248 | [Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample](https://huggingface.co/datasets/Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample) |
-| `LeData/media-metadata-artists` | 111 | [LeData/media-metadata-artists](https://huggingface.co/datasets/LeData/media-metadata-artists) |
-| `lukealvess/forex-algotrading-m15-1000-columns` | 9 | [lukealvess/forex-algotrading-m15-1000-columns](https://huggingface.co/datasets/lukealvess/forex-algotrading-m15-1000-columns) |
-| `mandarjoshi/trivia_qa` | 5 | [mandarjoshi/trivia_qa](https://huggingface.co/datasets/mandarjoshi/trivia_qa) |
-| `mariozupan/bookkeeping-posting-schemes-2007-2023` | 51 | [mariozupan/bookkeeping-posting-schemes-2007-2023](https://huggingface.co/datasets/mariozupan/bookkeeping-posting-schemes-2007-2023) |
-| `matzejo/godot-lora-dataset` | 144 | [matzejo/godot-lora-dataset](https://huggingface.co/datasets/matzejo/godot-lora-dataset) |
-| `MCES10-Software/SwiftUI-Code-Examples` | 201 | [MCES10-Software/SwiftUI-Code-Examples](https://huggingface.co/datasets/MCES10-Software/SwiftUI-Code-Examples) |
-| `mercor/apex-accounting` | 9 | [mercor/apex-accounting](https://huggingface.co/datasets/mercor/apex-accounting) |
-| `mikegarts/oa_tell_a_joke_20000` | 114 | [mikegarts/oa_tell_a_joke_20000](https://huggingface.co/datasets/mikegarts/oa_tell_a_joke_20000) |
-| `MindOSProducer/Mind-OS-33-Protocols` | 25 | [MindOSProducer/Mind-OS-33-Protocols](https://huggingface.co/datasets/MindOSProducer/Mind-OS-33-Protocols) |
-| `MLBtrio/genz-slang-dataset` | 54 | [MLBtrio/genz-slang-dataset](https://huggingface.co/datasets/MLBtrio/genz-slang-dataset) |
-| `MuratcanKoylan/MarketingStructuralPrompts` | 536 | [MuratcanKoylan/MarketingStructuralPrompts](https://huggingface.co/datasets/MuratcanKoylan/MarketingStructuralPrompts) |
-| `MuratKomurcu/stm32-hal-dataset` | 369 | [MuratKomurcu/stm32-hal-dataset](https://huggingface.co/datasets/MuratKomurcu/stm32-hal-dataset) |
-| `nebulatech/pharma-digital-marketing-dataset` | 1 | [nebulatech/pharma-digital-marketing-dataset](https://huggingface.co/datasets/nebulatech/pharma-digital-marketing-dataset) |
-| `neural-bridge/rag-dataset-1200` | 94 | [neural-bridge/rag-dataset-1200](https://huggingface.co/datasets/neural-bridge/rag-dataset-1200) |
-| `nibeditans/crros-customer-behavior-dataset` | 600 | [nibeditans/crros-customer-behavior-dataset](https://huggingface.co/datasets/nibeditans/crros-customer-behavior-dataset) |
-| `nvidia/AudioSkills` | 10 | [nvidia/AudioSkills](https://huggingface.co/datasets/nvidia/AudioSkills) |
-| `odemzkolo/flaws-cloudtrail-security-qa` | 109 | [odemzkolo/flaws-cloudtrail-security-qa](https://huggingface.co/datasets/odemzkolo/flaws-cloudtrail-security-qa) |
-| `pdfqa/pdfQA-Annotations` | 83 | [pdfqa/pdfQA-Annotations](https://huggingface.co/datasets/pdfqa/pdfQA-Annotations) |
-| `propfirmkey/prop-trading-qa-conversational-ai` | 50 | [propfirmkey/prop-trading-qa-conversational-ai](https://huggingface.co/datasets/propfirmkey/prop-trading-qa-conversational-ai) |
-| `RafaM97/marketing_social_media` | 672 | [RafaM97/marketing_social_media](https://huggingface.co/datasets/RafaM97/marketing_social_media) |
-| `reddit-tools-HF/reddit-bestofredditorupdates-processed` | 45 | [reddit-tools-HF/reddit-bestofredditorupdates-processed](https://huggingface.co/datasets/reddit-tools-HF/reddit-bestofredditorupdates-processed) |
-| `referencesource/router-firmware-support-status` | 260 | [referencesource/router-firmware-support-status](https://huggingface.co/datasets/referencesource/router-firmware-support-status) |
-| `reknine69/QA-citations` | 176 | [reknine69/QA-citations](https://huggingface.co/datasets/reknine69/QA-citations) |
-| `reloading0101/threat-intelligence-dataset` | 917 | [reloading0101/threat-intelligence-dataset](https://huggingface.co/datasets/reloading0101/threat-intelligence-dataset) |
-| `Richarddzz/NSFW-Chinese-Adult-Image-Caption` | 7 | [Richarddzz/NSFW-Chinese-Adult-Image-Caption](https://huggingface.co/datasets/Richarddzz/NSFW-Chinese-Adult-Image-Caption) |
-| `rx1lora/StoryPlay_RolePlay-NPCv2` | 9 | [rx1lora/StoryPlay_RolePlay-NPCv2](https://huggingface.co/datasets/rx1lora/StoryPlay_RolePlay-NPCv2) |
-| `Salesforce/wikitext` | 248 | [Salesforce/wikitext](https://huggingface.co/datasets/Salesforce/wikitext) |
-| `samuelandaudreymedianetwork/partnerships-and-media-references` | 45 | [samuelandaudreymedianetwork/partnerships-and-media-references](https://huggingface.co/datasets/samuelandaudreymedianetwork/partnerships-and-media-references) |
-| `sangamdas/Execution-Finality-Security-for-Agentic-AI-Autonomous-Systems-Cloud-Payments-Telecom-OS-and-Robo` | 85 | [sangamdas/Execution-Finality-Security-for-Agentic-AI-Autonomous-Systems-Cloud-Payments-Telecom-OS-and-Robo](https://huggingface.co/datasets/sangamdas/Execution-Finality-Security-for-Agentic-AI-Autonomous-Systems-Cloud-Payments-Telecom-OS-and-Robo) |
-| `sergiogpinto/memefact-templates` | 94 | [sergiogpinto/memefact-templates](https://huggingface.co/datasets/sergiogpinto/memefact-templates) |
-| `shahryars/vazirweb-persian-social-media-content` | 9 | [shahryars/vazirweb-persian-social-media-content](https://huggingface.co/datasets/shahryars/vazirweb-persian-social-media-content) |
-| `SicariusSicariiStuff/Bluemoon_Top50MB_Sorted_Fixed` | 10 | [SicariusSicariiStuff/Bluemoon_Top50MB_Sorted_Fixed](https://huggingface.co/datasets/SicariusSicariiStuff/Bluemoon_Top50MB_Sorted_Fixed) |
-| `sidddd625/adaption-business-compliance-qa-in-devanagri-script` | 8 | [sidddd625/adaption-business-compliance-qa-in-devanagri-script](https://huggingface.co/datasets/sidddd625/adaption-business-compliance-qa-in-devanagri-script) |
-| `socialmediaie/SocialMediaIE-MetaCorpus-v1` | 244 | [socialmediaie/SocialMediaIE-MetaCorpus-v1](https://huggingface.co/datasets/socialmediaie/SocialMediaIE-MetaCorpus-v1) |
-| `starknet-ai/cairo-security-audits` | 133 | [starknet-ai/cairo-security-audits](https://huggingface.co/datasets/starknet-ai/cairo-security-audits) |
-| `stindardlogic/brainstorming-ideation-sft-100k` | 99 | [stindardlogic/brainstorming-ideation-sft-100k](https://huggingface.co/datasets/stindardlogic/brainstorming-ideation-sft-100k) |
-| `Svngoku/adaption-african-research-literature-current-events-qa` | 34 | [Svngoku/adaption-african-research-literature-current-events-qa](https://huggingface.co/datasets/Svngoku/adaption-african-research-literature-current-events-qa) |
-| `tahamajs/bitcoin-investment-advisory-dataset` | 10 | [tahamajs/bitcoin-investment-advisory-dataset](https://huggingface.co/datasets/tahamajs/bitcoin-investment-advisory-dataset) |
-| `th1nhng0/vietnamese-legal-documents` | 86 | [th1nhng0/vietnamese-legal-documents](https://huggingface.co/datasets/th1nhng0/vietnamese-legal-documents) |
-| `thisnick/nsfw-video-still-caption-grid-only` | 101 | [thisnick/nsfw-video-still-caption-grid-only](https://huggingface.co/datasets/thisnick/nsfw-video-still-caption-grid-only) |
-| `uncledecart/rtos` | 10 | [uncledecart/rtos](https://huggingface.co/datasets/uncledecart/rtos) |
-| `Uris001/equity-research-dataset` | 58 | [Uris001/equity-research-dataset](https://huggingface.co/datasets/Uris001/equity-research-dataset) |
-| `victorzarzu/interior-design-prompt-editing-dataset-test` | 23 | [victorzarzu/interior-design-prompt-editing-dataset-test](https://huggingface.co/datasets/victorzarzu/interior-design-prompt-editing-dataset-test) |
-| `vishnuOI/unity-dev-instructions` | 142 | [vishnuOI/unity-dev-instructions](https://huggingface.co/datasets/vishnuOI/unity-dev-instructions) |
-| `yatin-superintelligence/Edge-Agent-Reasoning-WebSearch-260K` | 12 | [yatin-superintelligence/Edge-Agent-Reasoning-WebSearch-260K](https://huggingface.co/datasets/yatin-superintelligence/Edge-Agent-Reasoning-WebSearch-260K) |
-| `Yoav-omer/startups` | 1,168 | [Yoav-omer/startups](https://huggingface.co/datasets/Yoav-omer/startups) |
-| `YUXCulturalAILab/senegal-maternal-health-qa` | 7 | [YUXCulturalAILab/senegal-maternal-health-qa](https://huggingface.co/datasets/YUXCulturalAILab/senegal-maternal-health-qa) |
-## Additional run-2 / run-3 sources
-These rows account for all 10,350 uses from the additional external-source pool, reconciled against the per-record training backup.
-| Source | Individually recoverable uses |
-|---|---:|
-| [HuggingFaceH4/no_robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots) | 3,175 |
-| [MegaScience/TextbookReasoning](https://huggingface.co/datasets/MegaScience/TextbookReasoning) | 5,000 |
-| [allenai/ai2_arc](https://huggingface.co/datasets/allenai/ai2_arc) | 450 |
-| [allenai/qasc](https://huggingface.co/datasets/allenai/qasc) | 450 |
-| [heyalexchoi/qwen3-math-concise-sft-v3](https://huggingface.co/datasets/heyalexchoi/qwen3-math-concise-sft-v3) | 375 |
-| [openai/gsm8k](https://huggingface.co/datasets/openai/gsm8k) | 900 |
-## Attribution notes
-Source URLs identify attribution, not an endorsement or a claim of complete license review. Some retained adapters have no recoverable upstream URL; these are explicitly marked rather than linked to a guessed dataset. Original release lineage is documented in the model card.

+# Dataset sources
+This list attributes the sources recorded for the three training runs (6,000 / 12,000 / 16,000 uses). A record use is not necessarily a unique image or example. Selected samples were used, not entire upstream datasets. Follow each source page for its description and licensing; those licenses are not replaced by the model license.
+## Private, manually prepared packages
+| Package | Recorded uses | Source |
+|---|---:|---|
+| Broad adult learning | 3,070 | Private curation; not distributed |
+| Synthetic 3D model adult learning | 133 | Private synthetic multi-view groups; not distributed |
+## Public sources in the local training pool
+Counts are grouped by source adapter, so multiple rows can point to the same upstream dataset.
+| Source / adapter | Recorded uses | Source page |
+|---|---:|---|
+| `2796gauravc/agentic-search-data` | 176 | [2796gauravc/agentic-search-data](https://huggingface.co/datasets/2796gauravc/agentic-search-data) |
+| `A02_CHINESE_DIRECT_FRESH` | 6 | [Richarddzz/NSFW-Chinese-Adult-Image-Caption](https://huggingface.co/datasets/Richarddzz/NSFW-Chinese-Adult-Image-Caption) |
+| `A03_HDR` | 17 | [thisnick/nsfw-video-still-caption-grid-only](https://huggingface.co/datasets/thisnick/nsfw-video-still-caption-grid-only) |
+| `A03_VIDEO_STILLS` | 51 | [thisnick/nsfw-video-still-caption-grid-only](https://huggingface.co/datasets/thisnick/nsfw-video-still-caption-grid-only) |
+| `AfterQuery/FinanceQA` | 22 | [AfterQuery/FinanceQA](https://huggingface.co/datasets/AfterQuery/FinanceQA) |
+| `ahhany/constructionQAs` | 67 | [ahhany/constructionQAs](https://huggingface.co/datasets/ahhany/constructionQAs) |
+| `Ailiance-fr/mascarade-stm32-dataset` | 140 | [Ailiance-fr/mascarade-stm32-dataset](https://huggingface.co/datasets/Ailiance-fr/mascarade-stm32-dataset) |
+| `Alogotron/game-theory-business-strategy` | 1 | [Alogotron/game-theory-business-strategy](https://huggingface.co/datasets/Alogotron/game-theory-business-strategy) |
+| `AmazonScience/migration-bench-java-full` | 252 | [AmazonScience/migration-bench-java-full](https://huggingface.co/datasets/AmazonScience/migration-bench-java-full) |
+| `Atomic-Germ/Pygame-data` | 147 | [Atomic-Germ/Pygame-data](https://huggingface.co/datasets/Atomic-Germ/Pygame-data) |
+| `B01_VQARAD_DIRECT` | 40 | [abhay2812/vqa-rad](https://huggingface.co/datasets/abhay2812/vqa-rad) |
+| `B02_BODY_MEASUREMENTS_UNIQUEDATA_ADULT_DIRECT_0019` | 1 | [UniqueData/body-measurements-dataset](https://huggingface.co/datasets/UniqueData/body-measurements-dataset) |
+| `B02_FASHION_DE` | 52 | [jinaai/fashion-captions-de](https://huggingface.co/datasets/jinaai/fashion-captions-de) |
+| `B02_HUMANPOSE_DENSEPOSE_SMALLDATA_DIRECT_0067` | 5 | [jschoormans/humanpose_densepose](https://huggingface.co/datasets/jschoormans/humanpose_densepose) |
+| `B03_CAULDRON_VISUAL7W` | 31 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B03_CAULDRON_VQAV2` | 32 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B04_CAULDRON_LNARR` | 34 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B04_CAULDRON_TEXTCAPS` | 29 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B05_CAPTCHA_HANDOFF_VENUSBENCH_0219` | 60 | [inclusionAI/VenusBench-CAPTCHA](https://huggingface.co/datasets/inclusionAI/VenusBench-CAPTCHA) |
+| `B05_ORCHARD_GUI` | 100 | [microsoft/Orchard](https://huggingface.co/datasets/microsoft/Orchard) |
+| `B05_UNIGUI1` | 15 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B05_UNIGUI2` | 15 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B06_CHARTQA` | 16 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B06_DOCVQA` | 18 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B06_GEOGUESSR_COUNTRY_CAPPED_0116` | 7 | [fren-gor/geoguessr-locations](https://huggingface.co/datasets/fren-gor/geoguessr-locations) |
+| `B06_INFOVQA` | 19 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B06_MAPQA` | 3 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B06_MEMES_HF_CAPPED_DEDUP` | 10 | [sin3142/memes-1500](https://huggingface.co/datasets/sin3142/memes-1500) |
+| `B06_OCRVQA` | 15 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B06_RENDERED` | 7 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B06_TEXTVQA` | 15 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B07_AKIS` | 13 | [OttomanNLP/Akis-Ottoman-Dataset](https://huggingface.co/datasets/OttomanNLP/Akis-Ottoman-Dataset) |
+| `B07_CHURRO` | 15 | [OttomanNLP/CHURRO-Ottoman-Turkish-Subset](https://huggingface.co/datasets/OttomanNLP/CHURRO-Ottoman-Turkish-Subset) |
+| `B07_PERSIAN` | 8 | [MR3z4/persian-handwriting-ocr](https://huggingface.co/datasets/MR3z4/persian-handwriting-ocr) |
+| `B08_CAULDRON_AI2D` | 21 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B08_OPEN_SCHEMATICS` | 82 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B09_3DCODE_DIRECT_CAPPED_0212` | 16 | [YipengGao/3DCode](https://huggingface.co/datasets/YipengGao/3DCode) |
+| `B09_CAP3D_ABO` | 17 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B10_AI2D` | 26 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B10_FIGUREQA` | 18 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B10_PLOTQA` | 12 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B10_SCIENCEQA` | 14 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B11_OPENWEBRL_REUSE` | 32 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B11_ORCHARD_SEQUENCE` | 3 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B12_CAULDRON_AOKVQA` | 19 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B12_CAULDRON_CLEVR` | 8 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B12_CAULDRON_COCOQA` | 18 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B12_CAULDRON_NLVR2` | 12 | [HuggingFaceM4/the_cauldron](https://huggingface.co/datasets/HuggingFaceM4/the_cauldron) |
+| `B12_CAULDRON_OKVQA` | 11 | Local adapter; exact upstream URL not recoverable from the retained source lock |
+| `B13_FACE_EXPRESSION_MIT_DIRECT_0392` | 4 | [Prasanna18/Human-Face_Images_for_Emotion_Recognition](https://huggingface.co/datasets/Prasanna18/Human-Face_Images_for_Emotion_Recognition) |
+| `Bakanayatsu/nsfw-image-public` | 1 | [Bakanayatsu/nsfw-image-public](https://huggingface.co/datasets/Bakanayatsu/nsfw-image-public) |
+| `bernabepuente/backend-api-instruction-dataset` | 132 | [bernabepuente/backend-api-instruction-dataset](https://huggingface.co/datasets/bernabepuente/backend-api-instruction-dataset) |
+| `BYC-Sophie/samsum-chatgpt-summary` | 46 | [BYC-Sophie/samsum-chatgpt-summary](https://huggingface.co/datasets/BYC-Sophie/samsum-chatgpt-summary) |
+| `CATIE-AQ/XMRec_reviews_fr_Electronics` | 972 | [CATIE-AQ/XMRec_reviews_fr_Electronics](https://huggingface.co/datasets/CATIE-AQ/XMRec_reviews_fr_Electronics) |
+| `Chat-Error/anime_pretraining_2` | 96 | [Chat-Error/anime_pretraining_2](https://huggingface.co/datasets/Chat-Error/anime_pretraining_2) |
+| `Christine-HiAiPerf/canadian-tax-law-qa` | 948 | [Christine-HiAiPerf/canadian-tax-law-qa](https://huggingface.co/datasets/Christine-HiAiPerf/canadian-tax-law-qa) |
+| `ChuckMcSneed/various_RP_system_prompts` | 87 | [ChuckMcSneed/various_RP_system_prompts](https://huggingface.co/datasets/ChuckMcSneed/various_RP_system_prompts) |
+| `ClarusC64/legal-advice-email-risk-option-instruction-coherence-v0.1` | 3 | [ClarusC64/legal-advice-email-risk-option-instruction-coherence-v0.1](https://huggingface.co/datasets/ClarusC64/legal-advice-email-risk-option-instruction-coherence-v0.1) |
+| `ClarusC64/legal-counsel-brief-fact-issue-instruction-coherence-risk-v0.1` | 4 | [ClarusC64/legal-counsel-brief-fact-issue-instruction-coherence-risk-v0.1](https://huggingface.co/datasets/ClarusC64/legal-counsel-brief-fact-issue-instruction-coherence-risk-v0.1) |
+| `ClarusC64/network-security-route-hijack-coherence-risk-v0.1` | 3 | [ClarusC64/network-security-route-hijack-coherence-risk-v0.1](https://huggingface.co/datasets/ClarusC64/network-security-route-hijack-coherence-risk-v0.1) |
+| `CollateralAnalytics/kgp-synthetic-customer-behavior-segments` | 1 | [CollateralAnalytics/kgp-synthetic-customer-behavior-segments](https://huggingface.co/datasets/CollateralAnalytics/kgp-synthetic-customer-behavior-segments) |
+| `community-datasets/europa_eac_tm` | 288 | [community-datasets/europa_eac_tm](https://huggingface.co/datasets/community-datasets/europa_eac_tm) |
+| `contralabs/creative-ad-design-dataset` | 4 | [contralabs/creative-ad-design-dataset](https://huggingface.co/datasets/contralabs/creative-ad-design-dataset) |
+| `cowWhySo/pentest-redteam-steering` | 151 | [cowWhySo/pentest-redteam-steering](https://huggingface.co/datasets/cowWhySo/pentest-redteam-steering) |
+| `crazycog/linux-sysadmin-qa-askhole` | 78 | [crazycog/linux-sysadmin-qa-askhole](https://huggingface.co/datasets/crazycog/linux-sysadmin-qa-askhole) |
+| `crazycog/linux-sysadmin-qa-askhole-v1` | 782 | [crazycog/linux-sysadmin-qa-askhole-v1](https://huggingface.co/datasets/crazycog/linux-sysadmin-qa-askhole-v1) |
+| `CyberNative/Code_Vulnerability_Security_DPO` | 486 | [CyberNative/Code_Vulnerability_Security_DPO](https://huggingface.co/datasets/CyberNative/Code_Vulnerability_Security_DPO) |
+| `David-Chew-HL/Tech-Stocks-News` | 627 | [David-Chew-HL/Tech-Stocks-News](https://huggingface.co/datasets/David-Chew-HL/Tech-Stocks-News) |
+| `Draeg82/uk-gdpr-small-business-qa` | 242 | [Draeg82/uk-gdpr-small-business-qa](https://huggingface.co/datasets/Draeg82/uk-gdpr-small-business-qa) |
+| `electricsheepafrica/africa-south-sudan-global-subnational-population-statistics-f60bb180` | 71 | [electricsheepafrica/africa-south-sudan-global-subnational-population-statistics-f60bb180](https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-global-subnational-population-statistics-f60bb180) |
+| `electricsheepafrica/africa-synth-retail-and-ecommerce-supply-chain-logistics-data-nigeria` | 677 | [electricsheepafrica/africa-synth-retail-and-ecommerce-supply-chain-logistics-data-nigeria](https://huggingface.co/datasets/electricsheepafrica/africa-synth-retail-and-ecommerce-supply-chain-logistics-data-nigeria) |
+| `electricsheepafrica/africa-wearable-device-security` | 1,662 | [electricsheepafrica/africa-wearable-device-security](https://huggingface.co/datasets/electricsheepafrica/africa-wearable-device-security) |
+| `electricsheepafrica/africa-worldbank-wbl-supportive-framework-entrepreneurship-there-are-government-led-programs-sup` | 3 | [electricsheepafrica/africa-worldbank-wbl-supportive-framework-entrepreneurship-there-are-government-led-programs-sup](https://huggingface.co/datasets/electricsheepafrica/africa-worldbank-wbl-supportive-framework-entrepreneurship-there-are-government-led-programs-sup) |
+| `electricsheepafrica/nigerian_transport_and_logistics_environmental_impact` | 684 | [electricsheepafrica/nigerian_transport_and_logistics_environmental_impact](https://huggingface.co/datasets/electricsheepafrica/nigerian_transport_and_logistics_environmental_impact) |
+| `eniomecaj/embedded-systems-qa` | 138 | [eniomecaj/embedded-systems-qa](https://huggingface.co/datasets/eniomecaj/embedded-systems-qa) |
+| `facebook/asset` | 600 | [facebook/asset](https://huggingface.co/datasets/facebook/asset) |
+| `Falah/interior_design_prompts_SDXL` | 6 | [Falah/interior_design_prompts_SDXL](https://huggingface.co/datasets/Falah/interior_design_prompts_SDXL) |
+| `Finance-Agentic-AI/Portfolio-Rebalance` | 34 | [Finance-Agentic-AI/Portfolio-Rebalance](https://huggingface.co/datasets/Finance-Agentic-AI/Portfolio-Rebalance) |
+| `gjyotk/Menstrual-Health-Awareness-Dataset` | 105 | [gjyotk/Menstrual-Health-Awareness-Dataset](https://huggingface.co/datasets/gjyotk/Menstrual-Health-Awareness-Dataset) |
+| `google-research-datasets/aquamuse` | 175 | [google-research-datasets/aquamuse](https://huggingface.co/datasets/google-research-datasets/aquamuse) |
+| `google/mobile-actions` | 278 | [google/mobile-actions](https://huggingface.co/datasets/google/mobile-actions) |
+| `Gopher-Lab/huberman_lab_The_Science_of_Sexual_Development` | 1 | [Gopher-Lab/huberman_lab_The_Science_of_Sexual_Development](https://huggingface.co/datasets/Gopher-Lab/huberman_lab_The_Science_of_Sexual_Development) |
+| `greghavens/gpt-5.6-sol-coding-and-debugging-traces` | 49 | [greghavens/gpt-5.6-sol-coding-and-debugging-traces](https://huggingface.co/datasets/greghavens/gpt-5.6-sol-coding-and-debugging-traces) |
+| `gretelai/synthetic_pii_finance_multilingual` | 371 | [gretelai/synthetic_pii_finance_multilingual](https://huggingface.co/datasets/gretelai/synthetic_pii_finance_multilingual) |
+| `Gryphe/Opus-WritingPrompts` | 51 | [Gryphe/Opus-WritingPrompts](https://huggingface.co/datasets/Gryphe/Opus-WritingPrompts) |
+| `GyeongjuLee/instruction-tuning_EMH-emotional-reactions` | 20 | [GyeongjuLee/instruction-tuning_EMH-emotional-reactions](https://huggingface.co/datasets/GyeongjuLee/instruction-tuning_EMH-emotional-reactions) |
+| `Imrankhanjoya/ecommerce-onionpose` | 305 | [Imrankhanjoya/ecommerce-onionpose](https://huggingface.co/datasets/Imrankhanjoya/ecommerce-onionpose) |
+| `income/scidocs-top-20-gen-queries` | 889 | [income/scidocs-top-20-gen-queries](https://huggingface.co/datasets/income/scidocs-top-20-gen-queries) |
+| `infinite-dataset-hub/OvarianUltrasoundFeatureExtraction` | 3 | [infinite-dataset-hub/OvarianUltrasoundFeatureExtraction](https://huggingface.co/datasets/infinite-dataset-hub/OvarianUltrasoundFeatureExtraction) |
+| `introvoyz041/farmbot-arduino-firmware` | 1 | [introvoyz041/farmbot-arduino-firmware](https://huggingface.co/datasets/introvoyz041/farmbot-arduino-firmware) |
+| `ismailtasdelen/ethereum-smart-contract-security-qa` | 64 | [ismailtasdelen/ethereum-smart-contract-security-qa](https://huggingface.co/datasets/ismailtasdelen/ethereum-smart-contract-security-qa) |
+| `jjmachan/NSFW-questions-inter-cleaned_df` | 19 | [jjmachan/NSFW-questions-inter-cleaned_df](https://huggingface.co/datasets/jjmachan/NSFW-questions-inter-cleaned_df) |
+| `johndoe1100100101/nsfw_chat` | 3 | [johndoe1100100101/nsfw_chat](https://huggingface.co/datasets/johndoe1100100101/nsfw_chat) |
+| `Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample` | 248 | [Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample](https://huggingface.co/datasets/Karmane/bitnomial-crypto-derivatives-liquidity-funding-sample) |
+| `LeData/media-metadata-artists` | 111 | [LeData/media-metadata-artists](https://huggingface.co/datasets/LeData/media-metadata-artists) |
+| `lukealvess/forex-algotrading-m15-1000-columns` | 9 | [lukealvess/forex-algotrading-m15-1000-columns](https://huggingface.co/datasets/lukealvess/forex-algotrading-m15-1000-columns) |
+| `mandarjoshi/trivia_qa` | 5 | [mandarjoshi/trivia_qa](https://huggingface.co/datasets/mandarjoshi/trivia_qa) |
+| `mariozupan/bookkeeping-posting-schemes-2007-2023` | 51 | [mariozupan/bookkeeping-posting-schemes-2007-2023](https://huggingface.co/datasets/mariozupan/bookkeeping-posting-schemes-2007-2023) |
+| `matzejo/godot-lora-dataset` | 144 | [matzejo/godot-lora-dataset](https://huggingface.co/datasets/matzejo/godot-lora-dataset) |
+| `MCES10-Software/SwiftUI-Code-Examples` | 201 | [MCES10-Software/SwiftUI-Code-Examples](https://huggingface.co/datasets/MCES10-Software/SwiftUI-Code-Examples) |
+| `mercor/apex-accounting` | 9 | [mercor/apex-accounting](https://huggingface.co/datasets/mercor/apex-accounting) |
+| `mikegarts/oa_tell_a_joke_20000` | 114 | [mikegarts/oa_tell_a_joke_20000](https://huggingface.co/datasets/mikegarts/oa_tell_a_joke_20000) |
+| `MindOSProducer/Mind-OS-33-Protocols` | 25 | [MindOSProducer/Mind-OS-33-Protocols](https://huggingface.co/datasets/MindOSProducer/Mind-OS-33-Protocols) |
+| `MLBtrio/genz-slang-dataset` | 54 | [MLBtrio/genz-slang-dataset](https://huggingface.co/datasets/MLBtrio/genz-slang-dataset) |
+| `MuratcanKoylan/MarketingStructuralPrompts` | 536 | [MuratcanKoylan/MarketingStructuralPrompts](https://huggingface.co/datasets/MuratcanKoylan/MarketingStructuralPrompts) |
+| `MuratKomurcu/stm32-hal-dataset` | 369 | [MuratKomurcu/stm32-hal-dataset](https://huggingface.co/datasets/MuratKomurcu/stm32-hal-dataset) |
+| `nebulatech/pharma-digital-marketing-dataset` | 1 | [nebulatech/pharma-digital-marketing-dataset](https://huggingface.co/datasets/nebulatech/pharma-digital-marketing-dataset) |
+| `neural-bridge/rag-dataset-1200` | 94 | [neural-bridge/rag-dataset-1200](https://huggingface.co/datasets/neural-bridge/rag-dataset-1200) |
+| `nibeditans/crros-customer-behavior-dataset` | 600 | [nibeditans/crros-customer-behavior-dataset](https://huggingface.co/datasets/nibeditans/crros-customer-behavior-dataset) |
+| `nvidia/AudioSkills` | 10 | [nvidia/AudioSkills](https://huggingface.co/datasets/nvidia/AudioSkills) |
+| `odemzkolo/flaws-cloudtrail-security-qa` | 109 | [odemzkolo/flaws-cloudtrail-security-qa](https://huggingface.co/datasets/odemzkolo/flaws-cloudtrail-security-qa) |
+| `pdfqa/pdfQA-Annotations` | 83 | [pdfqa/pdfQA-Annotations](https://huggingface.co/datasets/pdfqa/pdfQA-Annotations) |
+| `propfirmkey/prop-trading-qa-conversational-ai` | 50 | [propfirmkey/prop-trading-qa-conversational-ai](https://huggingface.co/datasets/propfirmkey/prop-trading-qa-conversational-ai) |
+| `RafaM97/marketing_social_media` | 672 | [RafaM97/marketing_social_media](https://huggingface.co/datasets/RafaM97/marketing_social_media) |
+| `reddit-tools-HF/reddit-bestofredditorupdates-processed` | 45 | [reddit-tools-HF/reddit-bestofredditorupdates-processed](https://huggingface.co/datasets/reddit-tools-HF/reddit-bestofredditorupdates-processed) |
+| `referencesource/router-firmware-support-status` | 260 | [referencesource/router-firmware-support-status](https://huggingface.co/datasets/referencesource/router-firmware-support-status) |
+| `reknine69/QA-citations` | 176 | [reknine69/QA-citations](https://huggingface.co/datasets/reknine69/QA-citations) |
+| `reloading0101/threat-intelligence-dataset` | 917 | [reloading0101/threat-intelligence-dataset](https://huggingface.co/datasets/reloading0101/threat-intelligence-dataset) |
+| `Richarddzz/NSFW-Chinese-Adult-Image-Caption` | 7 | [Richarddzz/NSFW-Chinese-Adult-Image-Caption](https://huggingface.co/datasets/Richarddzz/NSFW-Chinese-Adult-Image-Caption) |
+| `rx1lora/StoryPlay_RolePlay-NPCv2` | 9 | [rx1lora/StoryPlay_RolePlay-NPCv2](https://huggingface.co/datasets/rx1lora/StoryPlay_RolePlay-NPCv2) |
+| `Salesforce/wikitext` | 248 | [Salesforce/wikitext](https://huggingface.co/datasets/Salesforce/wikitext) |
+| `samuelandaudreymedianetwork/partnerships-and-media-references` | 45 | [samuelandaudreymedianetwork/partnerships-and-media-references](https://huggingface.co/datasets/samuelandaudreymedianetwork/partnerships-and-media-references) |
+| `sangamdas/Execution-Finality-Security-for-Agentic-AI-Autonomous-Systems-Cloud-Payments-Telecom-OS-and-Robo` | 85 | [sangamdas/Execution-Finality-Security-for-Agentic-AI-Autonomous-Systems-Cloud-Payments-Telecom-OS-and-Robo](https://huggingface.co/datasets/sangamdas/Execution-Finality-Security-for-Agentic-AI-Autonomous-Systems-Cloud-Payments-Telecom-OS-and-Robo) |
+| `sergiogpinto/memefact-templates` | 94 | [sergiogpinto/memefact-templates](https://huggingface.co/datasets/sergiogpinto/memefact-templates) |
+| `shahryars/vazirweb-persian-social-media-content` | 9 | [shahryars/vazirweb-persian-social-media-content](https://huggingface.co/datasets/shahryars/vazirweb-persian-social-media-content) |
+| `SicariusSicariiStuff/Bluemoon_Top50MB_Sorted_Fixed` | 10 | [SicariusSicariiStuff/Bluemoon_Top50MB_Sorted_Fixed](https://huggingface.co/datasets/SicariusSicariiStuff/Bluemoon_Top50MB_Sorted_Fixed) |
+| `sidddd625/adaption-business-compliance-qa-in-devanagri-script` | 8 | [sidddd625/adaption-business-compliance-qa-in-devanagri-script](https://huggingface.co/datasets/sidddd625/adaption-business-compliance-qa-in-devanagri-script) |
+| `socialmediaie/SocialMediaIE-MetaCorpus-v1` | 244 | [socialmediaie/SocialMediaIE-MetaCorpus-v1](https://huggingface.co/datasets/socialmediaie/SocialMediaIE-MetaCorpus-v1) |
+| `starknet-ai/cairo-security-audits` | 133 | [starknet-ai/cairo-security-audits](https://huggingface.co/datasets/starknet-ai/cairo-security-audits) |
+| `stindardlogic/brainstorming-ideation-sft-100k` | 99 | [stindardlogic/brainstorming-ideation-sft-100k](https://huggingface.co/datasets/stindardlogic/brainstorming-ideation-sft-100k) |
+| `Svngoku/adaption-african-research-literature-current-events-qa` | 34 | [Svngoku/adaption-african-research-literature-current-events-qa](https://huggingface.co/datasets/Svngoku/adaption-african-research-literature-current-events-qa) |
+| `tahamajs/bitcoin-investment-advisory-dataset` | 10 | [tahamajs/bitcoin-investment-advisory-dataset](https://huggingface.co/datasets/tahamajs/bitcoin-investment-advisory-dataset) |
+| `th1nhng0/vietnamese-legal-documents` | 86 | [th1nhng0/vietnamese-legal-documents](https://huggingface.co/datasets/th1nhng0/vietnamese-legal-documents) |
+| `thisnick/nsfw-video-still-caption-grid-only` | 101 | [thisnick/nsfw-video-still-caption-grid-only](https://huggingface.co/datasets/thisnick/nsfw-video-still-caption-grid-only) |
+| `uncledecart/rtos` | 10 | [uncledecart/rtos](https://huggingface.co/datasets/uncledecart/rtos) |
+| `Uris001/equity-research-dataset` | 58 | [Uris001/equity-research-dataset](https://huggingface.co/datasets/Uris001/equity-research-dataset) |
+| `victorzarzu/interior-design-prompt-editing-dataset-test` | 23 | [victorzarzu/interior-design-prompt-editing-dataset-test](https://huggingface.co/datasets/victorzarzu/interior-design-prompt-editing-dataset-test) |
+| `vishnuOI/unity-dev-instructions` | 142 | [vishnuOI/unity-dev-instructions](https://huggingface.co/datasets/vishnuOI/unity-dev-instructions) |
+| `yatin-superintelligence/Edge-Agent-Reasoning-WebSearch-260K` | 12 | [yatin-superintelligence/Edge-Agent-Reasoning-WebSearch-260K](https://huggingface.co/datasets/yatin-superintelligence/Edge-Agent-Reasoning-WebSearch-260K) |
+| `Yoav-omer/startups` | 1,168 | [Yoav-omer/startups](https://huggingface.co/datasets/Yoav-omer/startups) |
+| `YUXCulturalAILab/senegal-maternal-health-qa` | 7 | [YUXCulturalAILab/senegal-maternal-health-qa](https://huggingface.co/datasets/YUXCulturalAILab/senegal-maternal-health-qa) |
+## Additional run-2 / run-3 sources
+These rows account for all 10,350 uses from the additional external-source pool, reconciled against the per-record training backup.
+| Source | Individually recoverable uses |
+|---|---:|
+| [HuggingFaceH4/no_robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots) | 3,175 |
+| [MegaScience/TextbookReasoning](https://huggingface.co/datasets/MegaScience/TextbookReasoning) | 5,000 |
+| [allenai/ai2_arc](https://huggingface.co/datasets/allenai/ai2_arc) | 450 |
+| [allenai/qasc](https://huggingface.co/datasets/allenai/qasc) | 450 |
+| [heyalexchoi/qwen3-math-concise-sft-v3](https://huggingface.co/datasets/heyalexchoi/qwen3-math-concise-sft-v3) | 375 |
+| [openai/gsm8k](https://huggingface.co/datasets/openai/gsm8k) | 900 |
+## Attribution notes
+Source URLs identify attribution, not an endorsement or a claim of complete license review. Some retained adapters have no recoverable upstream URL; these are explicitly marked rather than linked to a guessed dataset. Original release lineage is documented in the model card.

README.md CHANGED Viewed

@@ -1,157 +1,159 @@
----
-license: apache-2.0
-library_name: gguf
-pipeline_tag: image-text-to-text
-base_model: oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-FT
-tags:
-- qwen3_5_moe
-- vision
-- moe
-- conversational
-- not-for-all-audiences
-- abliterated
-- heretic
-- uncensor
-- hermes
-- mtp
-- coding
-- tool-calling
-- reasoning
-- roleplay
-- gguf
----
-# Qwen3.6-35B v2
-### 👁️ Understand images. 💻 Build things. 🎭 Make it personal.
-**Portable GGUF weights for llama.cpp.**
-[BF16 / FT](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-FT) · [GGUF / Llama](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama) · [Ollama](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Ollama) · [v2 collection](https://huggingface.co/collections/oktayd/qwen36-35b-v2-moe-uncensor-hermes-editions-6a9bcf212c664f52217f7ec5)
-## ✨ Meet the model
-Meet your local AI companion for ideas, code, images and conversation. **Qwen3.6-35B v2 by oktayd** brings these interests together in one downloadable model. Choose the edition that fits your setup, give it a task and shape its style with your own instructions.
-| | Focus |
-|---|---|
-| 🧠 Learn & explore | Ask about science, work through a problem or get an explanation in everyday language. |
-| 💻 Build & fix | Try a website idea, draft code or work through a bug together. |
-| 🛠️ Connect your tools | Use it in a tool-enabled app for structured requests and workflows. Your app supplies and executes the tools. |
-| 👁️ Bring an image | Ask about a screenshot, document, diagram or scene. |
-| 🎭 Set the personality | Explore stories, roleplay and different conversational styles through your instructions. |
-| 📦 Run it your way | Three editions and seven GGUF sizes, from compact experiments to higher-precision weights. |
-These are things to try, not promises of perfect results. It can make mistakes or repeat itself; check important answers. Adult-oriented training is included (**18+**).
-## 🕶️ Street knowledge. Business mind. Your style.
-The personality direction is **direct, sharp-witted and business-minded**: a street-smart conversation partner with humor, creative confidence and room for disagreement. The training mix includes internet culture, slang, practical business topics and personality-oriented conversations. Think less formal textbook, more an opinionated partner for brainstorming, writing and exploring alternatives.
-You set the tone: professional, casual, blunt or playful. The aim is personality without blind agreement. This is a style and training focus, not a guarantee of factual expertise or flawless judgment.
-## 🚀 Where should I start?
-| Your setup | Choose |
-|---|---|
-| I want a local chat app | [Ollama edition](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Ollama) and its guided importer |
-| I use llama.cpp or a compatible GGUF app | [GGUF / Llama edition](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama); Q4_K_M is a starting point if it fits your memory |
-| I work with Python or want the full weights | [BF16 / FT edition](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-FT) |
-Smaller files need less memory, but the lowest-bit versions can lose substantial quality. Vision needs the included image processor/projector as well as the language-model weights.
-### 💬 Try asking
-- “Explain this screenshot and suggest my next step.”
-- “Turn this idea into a simple website, then explain how to run it.”
-- “Find the bug in this function and show a corrected version.”
-- “Be a witty, direct writing partner and help develop this character.”
-## 📚 Training in brief
-**34,000 record uses in three runs:** broad knowledge, STEM, coding, tools and conversation, with selected visual examples. The private packages cover **synthetic 3D model adult learning** and **broad adult learning**; a small Chinese-caption sample complements the visual mix. [Dataset sources and training counts](DATASETS.md).
-## ⚙️ Architecture & validation
-<details>
-<summary>Technical specifications & validation</summary>
-- `Qwen3_5MoeForConditionalGeneration`; approximately 35B total parameters, 256 experts, 8 selected per token (the previous A3B label).
-- Native vision-language architecture; separate projector required for GGUF image input. Text and elementary red/blue-image smoke tests were recorded. Video, 3D consistency and full desktop/browser agents are not certified by those tests.
-- Training covered selected knowledge, instruction/agent, coding, personality and visual data: **34,000 record uses** across 6,000 + 12,000 + 16,000. Record uses are not unique records. Training loss is not benchmark accuracy.
-- All 19 source MTP tensors were preserved. **MTP/speculative acceleration is not enabled or validated by these benchmark results.** Backend support must be tested separately.
-- Tool-call formatting and end-of-answer behavior are diagnostic targets, not guaranteed features. Known schema mistakes, factual errors and repetition remain.
-</details>
-## 📦 Choose one quantization
-| Variant | Weight file | Size (GiB) | Status |
-|---|---|---:|---|
-| IQ1_M | [Qwen3.6-35B-v2-IQ1_M.gguf](Qwen3.6-35B-v2-IQ1_M.gguf) | 8.51 | experimental |
-| IQ2_M | [Qwen3.6-35B-v2-IQ2_M.gguf](Qwen3.6-35B-v2-IQ2_M.gguf) | 11.70 | experimental |
-| IQ4_XS | [Qwen3.6-35B-v2-IQ4_XS.gguf](Qwen3.6-35B-v2-IQ4_XS.gguf) | 17.86 | released; broad quant-specific quality untested |
-| Q3_K_M | [Qwen3.6-35B-v2-Q3_K_M.gguf](Qwen3.6-35B-v2-Q3_K_M.gguf) | 15.99 | released; broad quant-specific quality untested |
-| Q4_K_M | [Qwen3.6-35B-v2-Q4_K_M.gguf](Qwen3.6-35B-v2-Q4_K_M.gguf) | 20.22 | released; broad quant-specific quality untested |
-| Q5_K_M | [Qwen3.6-35B-v2-Q5_K_M.gguf](Qwen3.6-35B-v2-Q5_K_M.gguf) | 23.61 | released; broad quant-specific quality untested |
-| Q8_0 | [Qwen3.6-35B-v2-Q8_0.gguf](Qwen3.6-35B-v2-Q8_0.gguf) | 35.21 | released; broad quant-specific quality untested |
-Add `mmproj-Qwen3.6-35B-v2-F16.gguf` (about 0.84 GiB) for image input. File size is not runtime RAM/VRAM: KV cache, activations, projector, runtime and OS require extra memory.
-Q4_K_M/Q5_K_M/Q8_0 use standard llama.cpp quantization. IQ4_XS/Q3_K_M/IQ1_M/IQ2_M use a small mixed-text importance-matrix calibration, excluding benchmark prompts. All variants were created directly from BF16, not by requantizing a low-bit file. These are not Unsloth Dynamic or Bartowski-branded exports.
-**IQ1_M/IQ2_M are experimental.** Uncalibrated tensors, including MTP, stay at Q8_0; some MoE experts had incomplete calibration observations. The labels are not uniform bit widths for every weight. Substantial quality loss is possible. An IQ1_M smoke answer `7 + 5 = 12` was mathematically right but violated number-only formatting; the original strict result remains available.
-## 🚀 Run with llama.cpp
-Conversion/tested commit: `427291b5b34cd914a31b3fd3b61a68f6184f4b9f`.
-```bash
-llama-server -m Qwen3.6-35B-v2-Q4_K_M.gguf \
-  --mmproj mmproj-Qwen3.6-35B-v2-F16.gguf -ngl 99 -c 4096 -np 1 \
-  --host 127.0.0.1 --port 8080 \
-  --chat-template-kwargs '{"enable_thinking":false}'
-```
-This full-offload example needs enough VRAM. Lower offload on smaller devices; do not assume a 16-GB GPU holds the complete Q4 model. Chat/tokenizer metadata are embedded in the GGUF. Use per-request `max_tokens` and a client watchdog. These cap runaway generation but do not fix wrong reasoning.
-## 🧰 Support files and known limitations
-[SHA256SUMS](SHA256SUMS) verifies release files. [RELEASE-NAMING.json](RELEASE-NAMING.json) maps old repository/file names to v2 and records unchanged weight hashes. Historical validation reports intentionally retain their original runtime names; the map resolves those names. [RELEASE-SUMMARY.json](RELEASE-SUMMARY.json) and [GGUF-VALIDATION.json](GGUF-VALIDATION.json) record load, termination and elementary-answer checks separately.
-Thinking mode can loop; start with thinking off and bounded output. Guard stops are incomplete answers, not successful corrections. The private training inputs, installer ZIP, raw benchmark prompts/answers and internal debug logs are not part of these end-user repositories. Keep use within applicable rights and deployment requirements.
-## 📊 Measured diagnostics — scope matters
-<details>
-<summary>Measured results, comparison settings & limitations</summary>
-These are local **Q4_K_M / llama.cpp diagnostics**, not full official benchmark scores and not Ollama performance claims. Temperature 0, seed 42, thinking off, 16,384 context, 4,096 output cap, 45-second per-request budget. The RTX 2000 Ada used requested 24 GPU layers plus CPU offload; the actual offload-layer log was unavailable.
-| Model / device | Attempted / 204 | Completed | Old strict pass / scored | End-to-end output tok/s (median, outputs ≥64 tokens) |
-|---|---:|---:|---:|---:|
-| Q36 / H200 | 204 | 186 | 61 / 108 | 156.4 |
-| Q36 / RTX 5090 | 204 | 190 | 62 / 109 | 174.6 |
-| Huihui / RTX 5090 | 204 | 196 | 87 / 114 | 203.8 |
-| Q36 / RTX 2000 Ada (CPU+GPU) | 204 | 194 | 61 / 109 | 18.2 |
-| Huihui / RTX 2000 Ada (CPU+GPU) | 182 | 169 | 76 / 99 | 19.5 |
-These strict counts omit pending official/manual evaluators, use changing denominators, and sometimes reject semantically correct formatting variants. **Do not divide passes by all prompts or call these counts overall accuracy.** A separate local regrade keeps content, protocol compliance and delivery apart. It does not certify unreviewed reasoning or execute generated code. The Huihui RTX 2000 Ada run left 22 tasks untested at the global deadline. Earlier BF16 diagnostics used thinking and are not directly comparable.
-Huihui performed better on the shared automatically assessable RTX 5090 subset; no claim is made that this fine-tune universally surpasses its source or Qwen3.8. Rates mix generated lengths and are not pure hardware speedups. Native decode, prefill, client first-output and resource metrics are separated in [BENCHMARK-DEVICE-SUMMARY.json](BENCHMARK-DEVICE-SUMMARY.json). Raw prompts/answers and private training data are not published here.
-[Qwen3.8 comparison plan](BENCHMARK-PLAN.md) registers every benchmark family from the publisher card, including internal/unavailable tasks. **Qwen3.8 has not been tested locally.** Publisher scores use different harnesses, settings, annotations and trial counts and are shown only as references. No GPU job is launched by these support files.
-</details>
-## 📜 License, lineage & credits
-[Apache-2.0 license](LICENSE). Dataset sources and their own license information are linked in [DATASETS.md](DATASETS.md); model licensing does not relicense the source datasets. Thanks to the Qwen team, the inherited model and dataset authors, and the Soup, PEFT, Transformers, llama.cpp and Ollama projects.
-**Name guide:** `Qwen3.6-35B` identifies the model family and approximate total parameter count; `v2` is this project release; `MoE` means mixture of experts; `Ablit`, `Heretic`, `Uncensor` and `Hermes` describe inherited project lineage/training intent. `MTP` denotes preserved multi-token prediction weights, not a measured speedup; `Vision` denotes image-input support. `FT`, `Llama` and `Ollama` distinguish the three packages.
-These names do not imply affiliation or a promise of unrestricted behavior. Full provenance and validation are retained, including the historical Opus4.7-labelled source. No universal superiority, guaranteed compliance or removal of memorization is claimed.
-## 🔗 Related collection
-The previous release remains separate: [Qwen3.6 Opus4.7 Heretic Hermes Agent — Editions](https://huggingface.co/collections/oktayd/qwen36-opus47-heretic-hermes-agent-editions-6a8d09f6c2eb42ed1b112184).

+---
+license: apache-2.0
+library_name: gguf
+pipeline_tag: image-text-to-text
+base_model: oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-FT
+tags:
+- qwen3_5_moe
+- vision
+- moe
+- conversational
+- not-for-all-audiences
+- abliterated
+- heretic
+- uncensor
+- hermes
+- mtp
+- coding
+- tool-calling
+- reasoning
+- roleplay
+- gguf
+---
+# Qwen3.6-35B v2
+![Qwen3.6-35B v2 — Uncensored, Business, Tech, Vision, Dev — 18+](assets/qwen3.6-35b-v2-banner.png)
+### 👁️ Understand images. 💻 Build things. 🎭 Make it personal.
+**Portable GGUF weights for llama.cpp.**
+[BF16 / FT](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-FT) · [GGUF / Llama](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama) · [Ollama](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Ollama) · [v2 collection](https://huggingface.co/collections/oktayd/qwen36-35b-v2-moe-uncensor-hermes-editions-6a9bcf212c664f52217f7ec5)
+## ✨ Meet the model
+Meet your local AI companion for ideas, code, images and conversation. **Qwen3.6-35B v2 by oktayd** brings these interests together in one downloadable model. Choose the edition that fits your setup, give it a task and shape its style with your own instructions.
+| | Focus |
+|---|---|
+| 🧠 Learn & explore | Ask about science, work through a problem or get an explanation in everyday language. |
+| 💻 Build & fix | Try a website idea, draft code or work through a bug together. |
+| 🛠️ Connect your tools | Use it in a tool-enabled app for structured requests and workflows. Your app supplies and executes the tools. |
+| 👁️ Bring an image | Ask about a screenshot, document, diagram or scene. |
+| 🎭 Set the personality | Explore stories, roleplay and different conversational styles through your instructions. |
+| 📦 Run it your way | Three editions and seven GGUF sizes, from compact experiments to higher-precision weights. |
+These are things to try, not promises of perfect results. It can make mistakes or repeat itself; check important answers. Adult-oriented training is included (**18+**).
+## 🕶️ Street knowledge. Business mind. Your style.
+The personality direction is **direct, sharp-witted and business-minded**: a street-smart conversation partner with humor, creative confidence and room for disagreement. The training mix includes internet culture, slang, practical business topics and personality-oriented conversations. Think less formal textbook, more an opinionated partner for brainstorming, writing and exploring alternatives.
+You set the tone: professional, casual, blunt or playful. The aim is personality without blind agreement. This is a style and training focus, not a guarantee of factual expertise or flawless judgment.
+## 🚀 Where should I start?
+| Your setup | Choose |
+|---|---|
+| I want a local chat app | [Ollama edition](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Ollama) and its guided importer |
+| I use llama.cpp or a compatible GGUF app | [GGUF / Llama edition](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama); Q4_K_M is a starting point if it fits your memory |
+| I work with Python or want the full weights | [BF16 / FT edition](https://huggingface.co/oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-FT) |
+Smaller files need less memory, but the lowest-bit versions can lose substantial quality. Vision needs the included image processor/projector as well as the language-model weights.
+### 💬 Try asking
+- “Explain this screenshot and suggest my next step.”
+- “Turn this idea into a simple website, then explain how to run it.”
+- “Find the bug in this function and show a corrected version.”
+- “Be a witty, direct writing partner and help develop this character.”
+## 📚 Training in brief
+**34,000 record uses in three runs:** broad knowledge, STEM, coding, tools and conversation, with selected visual examples. The private packages cover **synthetic 3D model adult learning** and **broad adult learning**; a small Chinese-caption sample complements the visual mix. [Dataset sources and training counts](DATASETS.md).
+## ⚙️ Architecture & validation
+<details>
+<summary>Technical specifications & validation</summary>
+- `Qwen3_5MoeForConditionalGeneration`; approximately 35B total parameters, 256 experts, 8 selected per token (the previous A3B label).
+- Native vision-language architecture; separate projector required for GGUF image input. Text and elementary red/blue-image smoke tests were recorded. Video, 3D consistency and full desktop/browser agents are not certified by those tests.
+- Training covered selected knowledge, instruction/agent, coding, personality and visual data: **34,000 record uses** across 6,000 + 12,000 + 16,000. Record uses are not unique records. Training loss is not benchmark accuracy.
+- All 19 source MTP tensors were preserved. **MTP/speculative acceleration is not enabled or validated by these benchmark results.** Backend support must be tested separately.
+- Tool-call formatting and end-of-answer behavior are diagnostic targets, not guaranteed features. Known schema mistakes, factual errors and repetition remain.
+</details>
+## 📦 Choose one quantization
+| Variant | Weight file | Size (GiB) | Status |
+|---|---|---:|---|
+| IQ1_M | [Qwen3.6-35B-v2-IQ1_M.gguf](Qwen3.6-35B-v2-IQ1_M.gguf) | 8.51 | experimental |
+| IQ2_M | [Qwen3.6-35B-v2-IQ2_M.gguf](Qwen3.6-35B-v2-IQ2_M.gguf) | 11.70 | experimental |
+| IQ4_XS | [Qwen3.6-35B-v2-IQ4_XS.gguf](Qwen3.6-35B-v2-IQ4_XS.gguf) | 17.86 | released; broad quant-specific quality untested |
+| Q3_K_M | [Qwen3.6-35B-v2-Q3_K_M.gguf](Qwen3.6-35B-v2-Q3_K_M.gguf) | 15.99 | released; broad quant-specific quality untested |
+| Q4_K_M | [Qwen3.6-35B-v2-Q4_K_M.gguf](Qwen3.6-35B-v2-Q4_K_M.gguf) | 20.22 | released; broad quant-specific quality untested |
+| Q5_K_M | [Qwen3.6-35B-v2-Q5_K_M.gguf](Qwen3.6-35B-v2-Q5_K_M.gguf) | 23.61 | released; broad quant-specific quality untested |
+| Q8_0 | [Qwen3.6-35B-v2-Q8_0.gguf](Qwen3.6-35B-v2-Q8_0.gguf) | 35.21 | released; broad quant-specific quality untested |
+Add `mmproj-Qwen3.6-35B-v2-F16.gguf` (about 0.84 GiB) for image input. File size is not runtime RAM/VRAM: KV cache, activations, projector, runtime and OS require extra memory.
+Q4_K_M/Q5_K_M/Q8_0 use standard llama.cpp quantization. IQ4_XS/Q3_K_M/IQ1_M/IQ2_M use a small mixed-text importance-matrix calibration, excluding benchmark prompts. All variants were created directly from BF16, not by requantizing a low-bit file. These are not Unsloth Dynamic or Bartowski-branded exports.
+**IQ1_M/IQ2_M are experimental.** Uncalibrated tensors, including MTP, stay at Q8_0; some MoE experts had incomplete calibration observations. The labels are not uniform bit widths for every weight. Substantial quality loss is possible. An IQ1_M smoke answer `7 + 5 = 12` was mathematically right but violated number-only formatting; the original strict result remains available.
+## 🚀 Run with llama.cpp
+Conversion/tested commit: `427291b5b34cd914a31b3fd3b61a68f6184f4b9f`.
+```bash
+llama-server -m Qwen3.6-35B-v2-Q4_K_M.gguf \
+  --mmproj mmproj-Qwen3.6-35B-v2-F16.gguf -ngl 99 -c 4096 -np 1 \
+  --host 127.0.0.1 --port 8080 \
+  --chat-template-kwargs '{"enable_thinking":false}'
+```
+This full-offload example needs enough VRAM. Lower offload on smaller devices; do not assume a 16-GB GPU holds the complete Q4 model. Chat/tokenizer metadata are embedded in the GGUF. Use per-request `max_tokens` and a client watchdog. These cap runaway generation but do not fix wrong reasoning.
+## 🧰 Support files and known limitations
+[SHA256SUMS](SHA256SUMS) verifies release files. [RELEASE-NAMING.json](RELEASE-NAMING.json) maps old repository/file names to v2 and records unchanged weight hashes. Historical validation reports intentionally retain their original runtime names; the map resolves those names. [RELEASE-SUMMARY.json](RELEASE-SUMMARY.json) and [GGUF-VALIDATION.json](GGUF-VALIDATION.json) record load, termination and elementary-answer checks separately.
+Thinking mode can loop; start with thinking off and bounded output. Guard stops are incomplete answers, not successful corrections. The private training inputs, installer ZIP, raw benchmark prompts/answers and internal debug logs are not part of these end-user repositories. Keep use within applicable rights and deployment requirements.
+## 📊 Measured diagnostics — scope matters
+<details>
+<summary>Measured results, comparison settings & limitations</summary>
+These are local **Q4_K_M / llama.cpp diagnostics**, not full official benchmark scores and not Ollama performance claims. Temperature 0, seed 42, thinking off, 16,384 context, 4,096 output cap, 45-second per-request budget. The RTX 2000 Ada used requested 24 GPU layers plus CPU offload; the actual offload-layer log was unavailable.
+| Model / device | Attempted / 204 | Completed | Old strict pass / scored | End-to-end output tok/s (median, outputs ≥64 tokens) |
+|---|---:|---:|---:|---:|
+| Q36 / H200 | 204 | 186 | 61 / 108 | 156.4 |
+| Q36 / RTX 5090 | 204 | 190 | 62 / 109 | 174.6 |
+| Huihui / RTX 5090 | 204 | 196 | 87 / 114 | 203.8 |
+| Q36 / RTX 2000 Ada (CPU+GPU) | 204 | 194 | 61 / 109 | 18.2 |
+| Huihui / RTX 2000 Ada (CPU+GPU) | 182 | 169 | 76 / 99 | 19.5 |
+These strict counts omit pending official/manual evaluators, use changing denominators, and sometimes reject semantically correct formatting variants. **Do not divide passes by all prompts or call these counts overall accuracy.** A separate local regrade keeps content, protocol compliance and delivery apart. It does not certify unreviewed reasoning or execute generated code. The Huihui RTX 2000 Ada run left 22 tasks untested at the global deadline. Earlier BF16 diagnostics used thinking and are not directly comparable.
+Huihui performed better on the shared automatically assessable RTX 5090 subset; no claim is made that this fine-tune universally surpasses its source or Qwen3.8. Rates mix generated lengths and are not pure hardware speedups. Native decode, prefill, client first-output and resource metrics are separated in [BENCHMARK-DEVICE-SUMMARY.json](BENCHMARK-DEVICE-SUMMARY.json). Raw prompts/answers and private training data are not published here.
+[Qwen3.8 comparison plan](BENCHMARK-PLAN.md) registers every benchmark family from the publisher card, including internal/unavailable tasks. **Qwen3.8 has not been tested locally.** Publisher scores use different harnesses, settings, annotations and trial counts and are shown only as references. No GPU job is launched by these support files.
+</details>
+## 📜 License, lineage & credits
+[Apache-2.0 license](LICENSE). Dataset sources and their own license information are linked in [DATASETS.md](DATASETS.md); model licensing does not relicense the source datasets. Thanks to the Qwen team, the inherited model and dataset authors, and the Soup, PEFT, Transformers, llama.cpp and Ollama projects.
+**Name guide:** `Qwen3.6-35B` identifies the model family and approximate total parameter count; `v2` is this project release; `MoE` means mixture of experts; `Ablit`, `Heretic`, `Uncensor` and `Hermes` describe inherited project lineage/training intent. `MTP` denotes preserved multi-token prediction weights, not a measured speedup; `Vision` denotes image-input support. `FT`, `Llama` and `Ollama` distinguish the three packages.
+These names do not imply affiliation or a promise of unrestricted behavior. Full provenance and validation are retained, including the historical Opus4.7-labelled source. No universal superiority, guaranteed compliance or removal of memorization is claimed.
+## 🔗 Related collection
+The previous release remains separate: [Qwen3.6 Opus4.7 Heretic Hermes Agent — Editions](https://huggingface.co/collections/oktayd/qwen36-opus47-heretic-hermes-agent-editions-6a8d09f6c2eb42ed1b112184).

SHA256SUMS CHANGED Viewed

@@ -2,7 +2,7 @@
 807d54b88902798393fc104c3ca80d3e424d64270e8d1e1a34a44d4574f52c7e  BENCHMARK-DIAGNOSTIC.json
 0e712dd8e4bc65088e170826e98bdc440fb19a2cfdb7613c643e9dabb624ecd8  BENCHMARK-EXTENSION-QWEN38.json
 67d070e3b12bcd185626054c81cdf4d528a9a1af26774050e1d50be370b5ee14  BENCHMARK-PLAN.md
-c9ec1ed3de66b798f53d7b478bcc9d1d8387df93c747de3f4ff56749b335a116  DATASETS.md
 5fa5bdc4687e5ed723af58eb436f545cc62589e5395d5041722639f03bb5ec9b  LAPTOP-BENCHMARK-MATRIX.json
 ad3521db2dbcdf0b2ff300349d312c0fb44a1ebccc84571712602c512bf4a733  Qwen3.6-35B-v2-IQ1_M.gguf
 61a1a351bdc64ad14616277b0f7c630abe297733a29d96659da3bb7b369c769d  Qwen3.6-35B-v2-IQ2_M.gguf
@@ -11,6 +11,7 @@ ad3521db2dbcdf0b2ff300349d312c0fb44a1ebccc84571712602c512bf4a733  Qwen3.6-35B-v2
 3cc8cd0bad0c37fba8e038f68c089cdf2e5f55619d48487fdd9bfff0686ef830  Qwen3.6-35B-v2-Q4_K_M.gguf
 a3a5b8afaf96d6d4c9dfb257e54406a04a8363791f980647f788c67ff3966615  Qwen3.6-35B-v2-Q5_K_M.gguf
 71099584272a77b22c4aa1152271bf7d85595e1b869ffc883440a9d0e225c073  Qwen3.6-35B-v2-Q8_0.gguf
-aab93e1db7c31769e4ee6474071dbfa55d2a2d55a3eced9011a0a44f9af37e07  README.md
 a69838e3728d2aa08941191fce1d7c5af6f0703a9a4444e8d6f0ef18cb4ecf8a  RELEASE-NAMING.json
 fc5f718f531acdfe2e45bb09655d40f525eab939f9a3ab501287758f901cb3ad  mmproj-Qwen3.6-35B-v2-F16.gguf

 807d54b88902798393fc104c3ca80d3e424d64270e8d1e1a34a44d4574f52c7e  BENCHMARK-DIAGNOSTIC.json
 0e712dd8e4bc65088e170826e98bdc440fb19a2cfdb7613c643e9dabb624ecd8  BENCHMARK-EXTENSION-QWEN38.json
 67d070e3b12bcd185626054c81cdf4d528a9a1af26774050e1d50be370b5ee14  BENCHMARK-PLAN.md
+5c1a6fa0bd2d21e400b4c84001abec8085e3f5d7fbe5d217e7a0af7f32f42c6d  DATASETS.md
 5fa5bdc4687e5ed723af58eb436f545cc62589e5395d5041722639f03bb5ec9b  LAPTOP-BENCHMARK-MATRIX.json
 ad3521db2dbcdf0b2ff300349d312c0fb44a1ebccc84571712602c512bf4a733  Qwen3.6-35B-v2-IQ1_M.gguf
 61a1a351bdc64ad14616277b0f7c630abe297733a29d96659da3bb7b369c769d  Qwen3.6-35B-v2-IQ2_M.gguf
 3cc8cd0bad0c37fba8e038f68c089cdf2e5f55619d48487fdd9bfff0686ef830  Qwen3.6-35B-v2-Q4_K_M.gguf
 a3a5b8afaf96d6d4c9dfb257e54406a04a8363791f980647f788c67ff3966615  Qwen3.6-35B-v2-Q5_K_M.gguf
 71099584272a77b22c4aa1152271bf7d85595e1b869ffc883440a9d0e225c073  Qwen3.6-35B-v2-Q8_0.gguf
+277c04f7ca2ff3d347a080e516dd6600f798048878003bf53fc7901d9d82b7b0  README.md
 a69838e3728d2aa08941191fce1d7c5af6f0703a9a4444e8d6f0ef18cb4ecf8a  RELEASE-NAMING.json
+d431e82d0ab961c261e525fc08fc3e64c0916fbd4d3f52b839b3d2eda0766338  assets/qwen3.6-35b-v2-banner.png
 fc5f718f531acdfe2e45bb09655d40f525eab939f9a3ab501287758f901cb3ad  mmproj-Qwen3.6-35B-v2-F16.gguf

assets/qwen3.6-35b-v2-banner.png ADDED Viewed

Git LFS Details

SHA256: d431e82d0ab961c261e525fc08fc3e64c0916fbd4d3f52b839b3d2eda0766338
Pointer size: 132 Bytes
Size of remote file: 2.01 MB