Instructions to use hf-tiny-model-private/tiny-random-MgpstrForSceneTextRecognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MgpstrForSceneTextRecognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-MgpstrForSceneTextRecognition")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MgpstrForSceneTextRecognition") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MgpstrForSceneTextRecognition") - Notebooks
- Google Colab
- Kaggle
File size: 678 Bytes
3c9c7b1 | 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 | {
"architectures": [
"MgpstrForSceneTextRecognition"
],
"attn_drop_rate": 0.0,
"distilled": false,
"drop_path_rate": 0.0,
"drop_rate": 0.0,
"hidden_size": 32,
"image_size": [
32,
128
],
"initializer_range": 0.02,
"layer_norm_eps": 1e-05,
"max_token_length": 27,
"mlp_ratio": 4.0,
"model_type": "mgp-str",
"num_attention_heads": 4,
"num_bpe_labels": 99,
"num_channels": 3,
"num_character_labels": 38,
"num_hidden_layers": 5,
"num_wordpiece_labels": 99,
"output_a3_attentions": false,
"output_hidden_states": null,
"patch_size": 4,
"qkv_bias": true,
"torch_dtype": "float32",
"transformers_version": "4.28.0.dev0"
}
|