Image-Text-to-Text
Transformers
Safetensors
qwen3_5_text
qwen3_5
text-generation
conversational
Eval Results
flm
fastflowlm
q4nx
npu2
Instructions to use Atomic-Germ/Ornith-1.0-9B-NPU2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atomic-Germ/Ornith-1.0-9B-NPU2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Atomic-Germ/Ornith-1.0-9B-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 AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Atomic-Germ/Ornith-1.0-9B-NPU2") model = AutoModelForMultimodalLM.from_pretrained("Atomic-Germ/Ornith-1.0-9B-NPU2", device_map="auto") 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?"} ] }, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Atomic-Germ/Ornith-1.0-9B-NPU2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Atomic-Germ/Ornith-1.0-9B-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/Ornith-1.0-9B-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/Ornith-1.0-9B-NPU2
- SGLang
How to use Atomic-Germ/Ornith-1.0-9B-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/Ornith-1.0-9B-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/Ornith-1.0-9B-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/Ornith-1.0-9B-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/Ornith-1.0-9B-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" } } ] } ] }' - Docker Model Runner
How to use Atomic-Germ/Ornith-1.0-9B-NPU2 with Docker Model Runner:
docker model run hf.co/Atomic-Germ/Ornith-1.0-9B-NPU2
|
Download README.md from Atomic-Germ/Ornith-1.0-9B-NPU2: direct link, hf CLI and curl.
- Browser
- Download file 1.84 kB
-
https://huggingface.co/Atomic-Germ/Ornith-1.0-9B-NPU2/resolve/main/README.md
- Command line
-
hf download hf://Atomic-Germ/Ornith-1.0-9B-NPU2/README.md
-
curl -L -o README.md https://huggingface.co/Atomic-Germ/Ornith-1.0-9B-NPU2/resolve/main/README.md
1.84 kB
| license: mit | |
| base_model: | |
| - ornith-ai/Ornith-1.0-9B | |
| base_model_relation: quantized | |
| quantized_by: Atomic-Germ | |
| pipeline_tag: image-text-to-text | |
| tags: | |
| - transformers | |
| - safetensors | |
| - qwen3_5 | |
| - image-text-to-text | |
| - text-generation | |
| - conversational | |
| - eval-results | |
| - flm | |
| - fastflowlm | |
| - q4nx | |
| - npu2 | |
| # *IF YOU USE COMMUNITY QWEN MODELS DO NOT UPGRADE TO FLM v1.0.2+* | |
| # Ornith-1.0-9B-NPU2 | |
| **FastFlowLM Q4NX conversion of [`ornith-ai/Ornith-1.0-9B`](https://huggingface.co/ornith-ai/Ornith-1.0-9B)** 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 | [`ornith-ai/Ornith-1.0-9B`](https://huggingface.co/ornith-ai/Ornith-1.0-9B) | | |
| | Weights | `model.q4nx` (7.11 GB) | | |
| | Modality | language / vision | | |
| | FLM version | `1.0.2` | | |
| | Converted | 2026-08-18 | | |
| ## 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` | |
| ```bash | |
| uv tool install flm-add | |
| flm-add Atomic-Germ/Ornith-1.0-9B-NPU2 --family qwen3.5 | |
| FLM_CONFIG_PATH="$HOME/.config/flm/model_list.json" FLM_XCLBIN_PATH="$HOME/.config/flm" flm run ornith:9b | |
| ``` | |
| ## 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: [ornith-ai/Ornith-1.0-9B](https://huggingface.co/ornith-ai/Ornith-1.0-9B) |