Instructions to use textattack/bert-base-uncased-ag-news with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-ag-news with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-ag-news")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-ag-news") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-ag-news") - Inference
- Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:231dd57bd3f926a6b5beef4daf3c3d084f3958fd25e216bc5cc0e2f4f9ef280c
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size 437991539
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