Image-Text-to-Text
MLX
Safetensors
multilingual
internvl_chat
vision-language
ocr
document-intelligence
qianfan
apple-silicon
custom_code
Eval Results
4-bit precision
Instructions to use jason1966/Qianfan-OCR-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use jason1966/Qianfan-OCR-MLX-4bit 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("jason1966/Qianfan-OCR-MLX-4bit") config = load_config("jason1966/Qianfan-OCR-MLX-4bit") # 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
| { | |
| "_valid_kwargs_names": [ | |
| "do_convert_rgb", | |
| "do_resize", | |
| "size", | |
| "size_divisor", | |
| "default_to_square", | |
| "resample", | |
| "do_rescale", | |
| "rescale_factor", | |
| "do_normalize", | |
| "image_mean", | |
| "image_std", | |
| "do_pad", | |
| "do_center_crop", | |
| "crop_size", | |
| "data_format", | |
| "input_data_format", | |
| "device" | |
| ], | |
| "crop_size": null, | |
| "data_format": "channels_first", | |
| "default_to_square": true, | |
| "device": null, | |
| "do_center_crop": null, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_pad": null, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "input_data_format": null, | |
| "model_valid_processing_keys": [ | |
| "do_convert_rgb", | |
| "do_resize", | |
| "size", | |
| "size_divisor", | |
| "default_to_square", | |
| "resample", | |
| "do_rescale", | |
| "rescale_factor", | |
| "do_normalize", | |
| "image_mean", | |
| "image_std", | |
| "do_pad", | |
| "do_center_crop", | |
| "crop_size", | |
| "data_format", | |
| "input_data_format", | |
| "device" | |
| ], | |
| "processor_class": "InternVLProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 384, | |
| "width": 384 | |
| }, | |
| "size_divisor": null, | |
| "video_processor_type": "InternVLVideoProcessor" | |
| } | |