Image-Text-to-Text
Transformers
GGUF
English
qwen3_5
qwen3.8-froggeric-v22.4
qwen3_5_text
conversational
q4nx
quantized
npu2
fastflowlm
fastflow
flm
empero-ai
qwen3.8
distillation
reasoning
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"
Download config.json from Atomic-Germ/Qwen3.8-Distilled-2B-NPU2: direct link, hf CLI and curl.
- Browser
- Download file 2.66 kB
-
https://huggingface.co/Atomic-Germ/Qwen3.8-Distilled-2B-NPU2/resolve/041841982ed2f8e620718c237cb233c8237eca6b/config.json
- Command line
-
hf download hf://Atomic-Germ/Qwen3.8-Distilled-2B-NPU2@041841982ed2f8e620718c237cb233c8237eca6b/config.json
-
curl -L -o config.json https://huggingface.co/Atomic-Germ/Qwen3.8-Distilled-2B-NPU2/resolve/041841982ed2f8e620718c237cb233c8237eca6b/config.json
2.66 kB
| { | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "attn_output_gate": true, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 248044, | |
| "full_attention_interval": 4, | |
| "head_dim": 256, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6144, | |
| "layer_types": [ | |
| "linear_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "full_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "full_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "full_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "full_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "full_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "linear_attention", | |
| "full_attention" | |
| ], | |
| "linear_conv_kernel_dim": 4, | |
| "linear_key_head_dim": 128, | |
| "linear_num_key_heads": 16, | |
| "linear_num_value_heads": 16, | |
| "linear_value_head_dim": 128, | |
| "max_position_embeddings": 262144, | |
| "mlp_only_layers": [], | |
| "model_type": "qwen3_5", | |
| "mtp_num_hidden_layers": 1, | |
| "mtp_use_dedicated_embeddings": false, | |
| "num_attention_heads": 8, | |
| "num_hidden_layers": 24, | |
| "num_key_value_heads": 2, | |
| "rms_norm_eps": 1e-06, | |
| "tie_word_embeddings": true, | |
| "use_cache": true, | |
| "vocab_size": 248320, | |
| "mamba_ssm_dtype": "float32", | |
| "rope_parameters": { | |
| "mrope_interleaved": true, | |
| "mrope_section": [ | |
| 11, | |
| 11, | |
| 10 | |
| ], | |
| "rope_type": "default", | |
| "rope_theta": 10000000, | |
| "partial_rotary_factor": 0.25 | |
| }, | |
| "addr_qk": 53248, | |
| "addr_kv": 53536, | |
| "flm_version": "1.0.1", | |
| "vision_model_weight": "vision_weight.q4nx", | |
| "vision_config": { | |
| "vision_mm_engine_xclbin_name": "vision_mm.xclbin", | |
| "vision_mha_engine_xclbin_name": "vision_attn.xclbin", | |
| "QWEN3_5_PATCH_SIZE": 16, | |
| "QWEN3_5_IMAGE_MERGE_SIZE": 2, | |
| "QWEN3_5_SPATIAL_MERGE_SIZE": 2, | |
| "QWEN3_5_SHORTEST_EDGE": 65536, | |
| "QWEN3_5_LONGEST_EDGE": 16777216, | |
| "QWEN3_5_VISION_RESCALE_FACTOR": 0.00392156862745098, | |
| "QWEN3_5_VISION_RESCALE_IMAGE_MEAN": 0.5, | |
| "QWEN3_5_VISION_RESCALE_IMAGE_STD": 0.5, | |
| "QWEN3_5_TEMPORAL_PATCH_SIZE": 2, | |
| "QWEN3_5_VISION_EMBED_DIM": 1024, | |
| "QWEN3_5_VISION_NUM_HEADS": 16, | |
| "QWEN3_5_VISION_HEAD_DIM": 64, | |
| "QWEN3_5_VISION_MLP_INTERMEDIATE_SIZE": 4096, | |
| "QWEN3_5_VISION_NUM_POSITION_EMBEDDINGS": 2304, | |
| "QWEN3_5_VISION_NUM_LAYERS": 24, | |
| "QWEN3_5_VISION_LAYER_NORM_EPSILON": 1e-06, | |
| "QWEN3_5_VISION_OUT_HIDDEN_SIZE": 2048, | |
| "VISION_MM_TILE_M": 128, | |
| "VISION_MM_TILE_K": 512, | |
| "VISION_MM_TILE_N": 64 | |
| } | |
| } |