Instructions to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 with HERMES:

# No code snippets available yet for this library.

# To use this model, check the repository files and the library's documentation.

# Want to help? PRs adding snippets are welcome at:
# https://github.com/huggingface/huggingface.js

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 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 jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4
# Run inference directly in the terminal:
llama cli -hf jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4
# Run inference directly in the terminal:
llama cli -hf jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

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 jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4
# Run inference directly in the terminal:
./llama-cli -hf jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

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 jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4
# Run inference directly in the terminal:
./build/bin/llama-cli -hf jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

Use Docker

docker model run hf.co/jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

LM Studio
Jan

vLLM

How to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4",
		"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/jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

Ollama
How to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 with Ollama:
```
ollama run hf.co/jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4
```
Unsloth Desktop

How to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

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": "jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 with Docker Model Runner:
```
docker model run hf.co/jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4
```

Lemonade

How to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

Run and chat with the model

lemonade run user.Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4-NVFP4

List all available models

lemonade list

Hermes Agent

How to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

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 jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4

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 "jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4:NVFP4" \
  --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"

Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final — NVFP4 GGUF

NVFP4 quantisation of LuffyTheFox/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-GGUF, built with advanced-gguf-quantizer (a llama.cpp fork focused on NVFP4 quantization).

Original Model & Genesis Tensor Repair: LuffyTheFox
Base Model: HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive (0/465 refusals)
Hermes Finetune: DJLougen/hermes-qwen3.5-35b-a3b-GGUF (transferred Hermes data onto the uncensored base)
Architecture: Mixture of Experts (MoE) — 35B total / ~3B active per token (8 routed + 1 shared)
Multimodal (Vision): Supported via mmproj-Hermes3.6-35B-A3B-Uncensored-Genesis.gguf

Files

v4 — Recommended (inline scales, LM Studio compatible)

File	Size	Tensors
`Hermes3.6-35B-A3B-Uncensored-Genesis-Final-NVFP4-v4.gguf`	~20 GB	733
`mmproj-Hermes3.6-35B-A3B-Uncensored-Genesis.gguf`	~899 MB	vision projector
`chat_template.jinja`	16 KB	chat template
`System_Prompt.txt`	6 KB	recommended system prompt
`System_Prompt_Agent.txt`	1 KB	agentic / tool-calling prompt
`System_Prompt_Creative.txt`	6 KB	creative prompt

v4 uses --nvfp4-inline-scales-only to emit native inline UE4M3 scales without separate .scale/.input_scale tensors. Required for LM Studio / Pelican and other runtimes that do not support the extended NVFP4 scale tensor contract.

Imatrix variants will follow after the plain v4 is confirmed working in target runtimes.

Source


Source GGUF	`Hermes3.6-35B-A3B-Uncensored-Genesis-Final-Q8_K_P.gguf` (43.6 GB, 10.06 BPW)
Architecture	`qwen35moe` (MoE), 40 layers
Context	262144
`general.file_type`	39 (`LLAMA_FTYPE_MOSTLY_NVFP4`)
MTP/NextN	none in source

Two-step pipeline: Q8_K_P → F16 intermediate → NVFP4. The F16 step gives the NVFP4 encoder clean data (no Q8 quantization noise). Quantised CPU-only (Ampere CUDA NVFP4 encoder hangs on MoE tensors).

Tensor mix (v4)

type	count	notes
F32	331	norms, ssm scalars, gate inputs
F16	175	sensitive weights (blk.0 attn, ssm, ffn_down_exps)
Q6_K	1	`output.weight`
NVFP4	226	bulk weights
total	733
separate `.scale`/`.input_scale`	0	inline UE4M3 only

Tensor protection policy

F16 singular-collapse protection:

tensor	type
`blk.0.attn_gate.weight`	F16
`blk.0.attn_qkv.weight`	F16
`blk.0.ffn_down_exps.weight`	F16
`blk.13.ffn_down_exps.weight`	F16

F32 architecture-specific protection:

all norm weights (attn/post_attention/q/k/ssm norms)
blk.*.ssm_conv1d.weight, blk.*.ssm_dt.bias, blk.*.ssm_a
blk.*.ffn_gate_inp_shexp.weight (shared expert gate input)
token_embd.weight → F16

Forced NVFP4 (do not push lower):

tensor	type
`blk.0.ssm_out.weight`	NVFP4
`blk.1.attn_gate.weight`	NVFP4
`blk.1.attn_qkv.weight`	NVFP4

Usage

llama-cli -m Hermes3.6-35B-A3B-Uncensored-Genesis-Final-NVFP4-v4.gguf \
  --mmproj mmproj-Hermes3.6-35B-A3B-Uncensored-Genesis.gguf \
  --jinja -c 131072 -ngl 99

Set K cache and V cache quantization to F16
GPU offload maximum, active experts 8
Use chat_template.jinja with --jinja; system prompts included in-repo

Hardware

Blackwell (RTX 50xx): native FP4 path, fastest
Ampere (RTX 30xx): NVFP4 inference works via fallback kernels

Reproducibility

# Step 1: Q8_K_P -> F16 intermediate
llama-quantize --allow-requantize \
  Hermes3.6-35B-A3B-Uncensored-Genesis-Final-Q8_K_P.gguf temp_f16.gguf F16 6

# Step 2: F16 -> NVFP4 v4 (inline scales only, CPU-only)
CUDA_VISIBLE_DEVICES="" llama-quantize \
  --allow-requantize \
  --nvfp4-inline-scales-only \
  --tensor-type-file tensor_types_protection.txt \
  temp_f16.gguf \
  Hermes3.6-35B-A3B-Uncensored-Genesis-Final-NVFP4-v4.gguf \
  NVFP4 6

Credits

Genesis algorithm & repair: LuffyTheFox
Base model: HauhauCS
Hermes dataset: NousResearch / DJLougen
NVFP4 quantisation: jan1k
Quantiser: advanced-gguf-quantizer

Downloads last month: 646

GGUF

Model size

35B params

Architecture

qwen35moe

Hardware compatibility

4-bit

Model tree for jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4

Base model

Qwen/Qwen3.6-35B-A3B

Quantized

HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

Quantized

(61)

this model

jan1k
/

Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4

Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final — NVFP4 GGUF

Files

v4 — Recommended (inline scales, LM Studio compatible)

Source

Tensor mix (v4)

Tensor protection policy

Usage

Hardware

Reproducibility

Credits

Model tree for jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4

Dataset used to train jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4