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: 768 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 | {
"model_type": "pp_ocrv5_server_rec",
"backbone_config": {
"model_type": "hgnet_v2",
"arch": "L",
"return_idx": [0, 1, 2, 3],
"freeze_stem_only": true,
"freeze_at": 0,
"freeze_norm": true,
"lr_mult_list": [1.0, 1.0, 1.0, 1.0, 1.0],
"out_features": ["stage1", "stage2", "stage3", "stage4"],
"stage_downsample": [true, true, true, true],
"stem_strides": [2, 1, 1, 1, 1],
"stage_downsample_strides": [[2, 1], [1, 2], [2, 1], [2, 1]]
},
"hidden_act": "silu",
"hidden_size": 120,
"mlp_ratio": 2.0,
"depth": 2,
"head_out_channels": 18385,
"conv_kernel_size": [1, 3],
"qkv_bias": true,
"num_attention_heads": 8,
"attention_dropout": 0.0
} |