Instructions to use textattack/bert-base-uncased-snli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-snli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-snli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-snli") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-snli") - Notebooks
- Google Colab
- Kaggle
Update train_args.json
Browse files- train_args.json +1 -1
train_args.json
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@@ -2,5 +2,5 @@
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"model": "bert-base-uncased",
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"dataset": "snli",
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"num_labels": 3,
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"dataset_dev_split": "validation"
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}
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"model": "bert-base-uncased",
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"dataset": "snli",
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"num_labels": 3,
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"dataset_dev_split": "validation"
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}
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