Image-Text-to-Text
MLX
Safetensors
multilingual
unlimited-ocr
baidu
vision-language
ocr
custom_code
mlx-vlm
quantized
affine-quantization
8-bit precision
conversational
8-bit precision
Instructions to use mlx-community/Unlimited-OCR-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Unlimited-OCR-8bit 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("mlx-community/Unlimited-OCR-8bit") config = load_config("mlx-community/Unlimited-OCR-8bit") # 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
- Atomic Chat
File size: 464 Bytes
677193d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"add_special_token": false,
"candidate_resolutions": [
[
1024,
1024
]
],
"downsample_ratio": 4,
"ignore_id": -100,
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"image_token": "<image>",
"mask_prompt": false,
"normalize": true,
"pad_token": "<\uff5c\u2581pad\u2581\uff5c>",
"patch_size": 16,
"processor_class": "UnlimitedOCRProcessor",
"sft_format": "unlimitedocr"
}
|