Instructions to use textattack/bert-base-uncased-MNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-MNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-MNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-MNLI") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-MNLI") - Inference
- Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:02fa27735990e212439ec04be82931059be4af278b33427bbb42a316919543b7
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size 437988463
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