Instructions to use pruhtopia/bert-toc-classification-95k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pruhtopia/bert-toc-classification-95k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pruhtopia/bert-toc-classification-95k")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pruhtopia/bert-toc-classification-95k") model = AutoModelForSequenceClassification.from_pretrained("pruhtopia/bert-toc-classification-95k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Model Trained Using AutoTrain
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- Problem type: Text Classification
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## Validation Metrics
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loss: 0.5102838277816772
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# Model Trained Using AutoTrain
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- Problem type: Text Classification
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- Task: Legal Document Sequence Classification
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- id2label: [0: 'Caption',
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1: 'Footnote',
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2: 'Formula',
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3: 'List-item',
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4: 'Page-footer',
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5: 'Page-header',
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6: 'Picture',
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7: 'Section-header',
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8: 'Table',
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9: 'Text',
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10: 'Title']
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## Validation Metrics
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loss: 0.5102838277816772
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