Instructions to use Zyphra/ZAYA1-VL-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zyphra/ZAYA1-VL-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Zyphra/ZAYA1-VL-8B") 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 AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("Zyphra/ZAYA1-VL-8B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Zyphra/ZAYA1-VL-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Zyphra/ZAYA1-VL-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Zyphra/ZAYA1-VL-8B", "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/Zyphra/ZAYA1-VL-8B
- SGLang
How to use Zyphra/ZAYA1-VL-8B 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 "Zyphra/ZAYA1-VL-8B" \ --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": "Zyphra/ZAYA1-VL-8B", "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 "Zyphra/ZAYA1-VL-8B" \ --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": "Zyphra/ZAYA1-VL-8B", "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 Zyphra/ZAYA1-VL-8B with Docker Model Runner:
docker model run hf.co/Zyphra/ZAYA1-VL-8B
File size: 881 Bytes
769048c | 1 2 3 4 | {
"chat_template": "{% for message in messages %}{% if message['role'] == 'user' %}{% for content in message['content'] | selectattr('type', 'equalto', 'image') %}{{ '<|vision_start|><image><|vision_end|>\\n' }}{% endfor %}{% for content in message['content'] | selectattr('type', 'equalto', 'text') %}{{ '<|im_start|>' ~ message['role'] ~ '\n' ~ content['text'] ~ '<|im_end|>' ~ '\n' }}{% endfor %}{% elif message['role'] == 'question' %}{{ '<|im_start|>user\\n' }}{% for content in message['content'] | selectattr('type', 'equalto', 'text') %}{{ content['text'] ~ '<|im_end|>\\n' }}{% endfor %}{% else %}{{ '<|im_start|>' ~ message['role'] ~ '\\n' }}{% for content in message['content'] | selectattr('type', 'equalto', 'text') %}{{ content['text'] ~ '<|im_end|>' }}{% endfor %}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\\n' }}{% endif %}"
}
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