Instructions to use ornith-ai/Ornith-1.5-35B-A3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ornith-ai/Ornith-1.5-35B-A3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ornith-ai/Ornith-1.5-35B-A3B") 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 AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ornith-ai/Ornith-1.5-35B-A3B") model = AutoModelForMultimodalLM.from_pretrained("ornith-ai/Ornith-1.5-35B-A3B", 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 = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ornith-ai/Ornith-1.5-35B-A3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ornith-ai/Ornith-1.5-35B-A3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ornith-ai/Ornith-1.5-35B-A3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ornith-ai/Ornith-1.5-35B-A3B
- SGLang
How to use ornith-ai/Ornith-1.5-35B-A3B 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 "ornith-ai/Ornith-1.5-35B-A3B" \ --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": "ornith-ai/Ornith-1.5-35B-A3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "ornith-ai/Ornith-1.5-35B-A3B" \ --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": "ornith-ai/Ornith-1.5-35B-A3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ornith-ai/Ornith-1.5-35B-A3B with Docker Model Runner:
docker model run hf.co/ornith-ai/Ornith-1.5-35B-A3B
Removed Vision Capabilities
#7
by tushar310 - opened
Hi,
Could you please help us understand if vision capabilities have been removed to make it faster? It seems that ways only thus the question. Qwen3.6 , Gemma4... both series supports thinking toggles, vision capabilities and tool use. Could you suggest how does the same work on yours or have you removed it altogether?
Wdym? just use Qwen 3.6 mmproj file..
Yes, I've feed it image with errors and it read it and identified them correctly.