Instructions to use textattack/bert-base-uncased-rotten-tomatoes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-rotten-tomatoes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-rotten-tomatoes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-rotten-tomatoes") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-rotten-tomatoes") - Notebooks
- Google Colab
- Kaggle
Commit ·
2aeb2b0
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Parent(s): fcddeba
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:7ea41714f440a138d145495a0c8f5d9e7c1a4d4af745b39d8109fc78761e94c9
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size 437942328
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