Image-to-Text
MLX
Safetensors
mlx-weights
paddlepaddle-ocr
ppocrv5
ppocrv6
ppdoclayoutv3
pp-structure
apple-silicon
Instructions to use plaincompute/ppocr-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use plaincompute/ppocr-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir ppocr-mlx plaincompute/ppocr-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 1,096 Bytes
1e1b9bd | 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 30 31 32 33 34 35 36 | {
"model_type": "pp_ocrv6_small_det",
"reduction": 4,
"layer_list_out_channels": [48, 96, 192, 384],
"neck_out_channels": 96,
"kernel_list": [3, 2, 2],
"interpolate_mode": "nearest",
"dilated_kernel_size": 7,
"backbone_config": {
"model_type": "pp_lcnet_v4",
"stem_channels": [3, 24, 48],
"stem_type": "large",
"out_features": ["stage1", "stage2", "stage3", "stage4"],
"out_indices": [1, 2, 3, 4],
"block_configs": [
[[3, 48, 48, 1, true], [3, 48, 48, 1, false]],
[
[3, 48, 96, 2, false],
[3, 96, 96, 1, true],
[3, 96, 96, 1, false]
],
[
[3, 96, 192, 2, false],
[3, 192, 192, 1, true],
[3, 192, 192, 1, false],
[3, 192, 192, 1, true],
[3, 192, 192, 1, false]
],
[
[3, 192, 384, 2, false],
[3, 384, 384, 1, true],
[3, 384, 384, 1, false]
]
]
}
} |