Instructions to use KennethTM/pix2struct-base-table2html with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KennethTM/pix2struct-base-table2html with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="KennethTM/pix2struct-base-table2html")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("KennethTM/pix2struct-base-table2html") model = AutoModelForImageTextToText.from_pretrained("KennethTM/pix2struct-base-table2html") - Notebooks
- Google Colab
- Kaggle
File size: 869 Bytes
38dbfb9 | 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 | {
"_name_or_path": "pix2struct-base-table2html",
"architectures": [
"Pix2StructForConditionalGeneration"
],
"decoder_start_token_id": 0,
"eos_token_id": 1,
"initializer_factor": 1.0,
"initializer_range": 0.02,
"is_encoder_decoder": true,
"is_vqa": false,
"model_type": "pix2struct",
"pad_token_id": 0,
"text_config": {
"dropout_rate": 0.2,
"encoder_hidden_size": 768,
"initializer_range": 0.02,
"model_type": "pix2struct_text_model"
},
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.42.1",
"vision_config": {
"attention_dropout": 0.2,
"dropout_rate": 0.2,
"hidden_dropout_prob": 0.2,
"initializer_range": 0.02,
"layer_norm_bias": false,
"model_type": "pix2struct_vision_model",
"num_channels": 3,
"patch_size": 16,
"projection_dim": 768
}
}
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