Instructions to use Tornaid/LayoutLMv2_D1_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tornaid/LayoutLMv2_D1_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tornaid/LayoutLMv2_D1_Classifier")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Tornaid/LayoutLMv2_D1_Classifier") model = AutoModelForSequenceClassification.from_pretrained("Tornaid/LayoutLMv2_D1_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 261 Bytes
6950998 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"apply_ocr": true,
"do_resize": true,
"image_processor_type": "LayoutLMv2FeatureExtractor",
"ocr_lang": null,
"processor_class": "LayoutLMv2Processor",
"resample": 2,
"size": {
"height": 224,
"width": 224
},
"tesseract_config": ""
}
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