Image-Text-to-Text
MLX
Safetensors
zaya1_vl
zaya
mixture-of-experts
hybrid-attention
cca-attention
apple-silicon
reasoning
tool-use
quantized
vision
multimodal
vision-language
qwen2_5_vl-vit
mxfp4
jang
osaurus
conversational
Instructions to use OsaurusAI/ZAYA1-VL-8B-MXFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use OsaurusAI/ZAYA1-VL-8B-MXFP4 with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("OsaurusAI/ZAYA1-VL-8B-MXFP4") config = load_config("OsaurusAI/ZAYA1-VL-8B-MXFP4") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
| { | |
| "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 %}" | |
| } | |