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
- Pi
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"
| { | |
| "schema_version": "q36.release-naming.v2", | |
| "release": { | |
| "repository": "oktayd/Qwen3.6-35B-v2-MoE-Ablit-Heretic-Uncensor-Hermes-MTP-Vision-Llama", | |
| "display_version": "v2", | |
| "weight_change": "none; this release renames the final GGUF exports from the documented v1.3 source revision", | |
| "source_repository": "oktayd/Q36-v1.3-35B-A3B-MTP-Vision-GGUF", | |
| "source_revision": "13e7d3c5baa212b19943d5f463add3be75065d0e" | |
| }, | |
| "historical_to_current_filename": { | |
| "Q36-v1.3-IQ1_M.gguf": "Qwen3.6-35B-v2-IQ1_M.gguf", | |
| "Q36-v1.3-IQ2_M.gguf": "Qwen3.6-35B-v2-IQ2_M.gguf", | |
| "Q36-v1.3-IQ4_XS.gguf": "Qwen3.6-35B-v2-IQ4_XS.gguf", | |
| "Q36-v1.3-Q3_K_M.gguf": "Qwen3.6-35B-v2-Q3_K_M.gguf", | |
| "Q36-v1.3-Q4_K_M.gguf": "Qwen3.6-35B-v2-Q4_K_M.gguf", | |
| "Q36-v1.3-Q5_K_M.gguf": "Qwen3.6-35B-v2-Q5_K_M.gguf", | |
| "Q36-v1.3-Q8_0.gguf": "Qwen3.6-35B-v2-Q8_0.gguf", | |
| "mmproj-Q36-v1.3-F16.gguf": "mmproj-Qwen3.6-35B-v2-F16.gguf" | |
| }, | |
| "weights": { | |
| "Qwen3.6-35B-v2-IQ1_M.gguf": { "bytes": 9138219072, "sha256": "ad3521db2dbcdf0b2ff300349d312c0fb44a1ebccc84571712602c512bf4a733", "experimental": true }, | |
| "Qwen3.6-35B-v2-IQ2_M.gguf": { "bytes": 12558245952, "sha256": "61a1a351bdc64ad14616277b0f7c630abe297733a29d96659da3bb7b369c769d", "experimental": true }, | |
| "Qwen3.6-35B-v2-IQ4_XS.gguf": { "bytes": 19179522112, "sha256": "80b45e93018023c6a9098cdee83f2a36ccc57dc490625cba2b783c6b3eb832cc", "experimental": false }, | |
| "Qwen3.6-35B-v2-Q3_K_M.gguf": { "bytes": 17166659648, "sha256": "99ad5dfecfea0da901074b4fdea4881382d2b0a3c431284d6cb19e54b55b9419", "experimental": false }, | |
| "Qwen3.6-35B-v2-Q4_K_M.gguf": { "bytes": 21713463040, "sha256": "3cc8cd0bad0c37fba8e038f68c089cdf2e5f55619d48487fdd9bfff0686ef830", "experimental": false }, | |
| "Qwen3.6-35B-v2-Q5_K_M.gguf": { "bytes": 25347532544, "sha256": "a3a5b8afaf96d6d4c9dfb257e54406a04a8363791f980647f788c67ff3966615", "experimental": false }, | |
| "Qwen3.6-35B-v2-Q8_0.gguf": { "bytes": 37802149632, "sha256": "71099584272a77b22c4aa1152271bf7d85595e1b869ffc883440a9d0e225c073", "experimental": false }, | |
| "mmproj-Qwen3.6-35B-v2-F16.gguf": { "bytes": 899283424, "sha256": "fc5f718f531acdfe2e45bb09655d40f525eab939f9a3ab501287758f901cb3ad", "experimental": false } | |
| } | |
| } | |