Instructions to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Atomic-Germ/Qwen3.8-Distilled-2B-NPU2") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Atomic-Germ/Qwen3.8-Distilled-2B-NPU2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 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 Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0 # Run inference directly in the terminal: llama cli -hf Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0 # Run inference directly in the terminal: llama cli -hf Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
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 Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
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 Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
Use Docker
docker model run hf.co/Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
- LM Studio
- Jan
- vLLM
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Atomic-Germ/Qwen3.8-Distilled-2B-NPU2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Atomic-Germ/Qwen3.8-Distilled-2B-NPU2", "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/Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
- SGLang
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Atomic-Germ/Qwen3.8-Distilled-2B-NPU2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Atomic-Germ/Qwen3.8-Distilled-2B-NPU2", "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 images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Atomic-Germ/Qwen3.8-Distilled-2B-NPU2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Atomic-Germ/Qwen3.8-Distilled-2B-NPU2", "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" } } ] } ] }' - Ollama
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with Ollama:
ollama run hf.co/Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
- Unsloth Desktop
- Pi
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
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": "Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with Docker Model Runner:
docker model run hf.co/Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
- Lemonade
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
Run and chat with the model
lemonade run user.Qwen3.8-Distilled-2B-NPU2-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
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 Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Atomic-Germ/Qwen3.8-Distilled-2B-NPU2 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0
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 "Atomic-Germ/Qwen3.8-Distilled-2B-NPU2:Q8_0" \ --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"
Qwen3.8-2B-Distill-NPU2
FastFlowLM Q4NX conversion of empero-ai/Qwen3.8-2B-Distill for AMD XDNA NPU inference.
This repository contains a quantized Q4NX port of the model, compiled for the FastFlowLM (FLM) runtime. It is not a GGUF file.
| Item | Value |
|---|---|
| Source model | empero-ai/Qwen3.8-2B-Distill |
| Source GGUF | Qwen3.8-2B-Q8_0.gguf |
| Weights | model.q4nx (2.32 GB) |
| Modality | language / vision |
| FLM version | 1.0.1 |
| Converted | 2026-08-24 |
Install and run
This repository works with flm-add, a small installer that copies the model
into the FastFlowLM user directory and registers the tag. It never
modifies the system FastFlowLM install.
pip install flm-add or uv tool install flm-add
uv tool install flm-add
flm-add Atomic-Germ/Qwen3.8-2B-Distill-NPU2 --family qwen3.5 --tag qwen3.8-distill:2b
FLM_CONFIG_PATH="$HOME/.config/flm/model_list.json" FLM_XCLBIN_PATH="$HOME/.config/flm" flm run qwen3.8-distill:2b
Files
| File | Description |
|---|---|
model.q4nx |
Quantized weights (Q8_0 / Q4_1 / BF16) |
config.json |
FLM runtime configuration |
tokenizer.json |
Tokenizer vocabulary |
tokenizer_config.json |
Tokenizer configuration |
chat_template.jinja |
Chat template |
vision_weight.q4nx |
Vision model |
Source model card
See the original model card: empero-ai/Qwen3.8-2B-Distill
- Downloads last month
- 169
8-bit