Image-Text-to-Text
MLX
Safetensors
multilingual
hunyuan_vl
ocr
hunyuan
vision-language
image-to-text
1B
apple-silicon
metal
conversational
Instructions to use AnandSingh/hunyuanocr-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AnandSingh/hunyuanocr-mlx 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("AnandSingh/hunyuanocr-mlx") config = load_config("AnandSingh/hunyuanocr-mlx") # 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 Settings
- LM Studio
| { | |
| "min_pixels": 262144, | |
| "max_pixels": 4194304, | |
| "patch_size": 16, | |
| "resample": 1, | |
| "temporal_patch_size": 1, | |
| "merge_size": 2, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "image_processor_type": "HunYuanVLImageProcessor", | |
| "processor_class": "HunYuanVLProcessor" | |
| } | |