Instructions to use textattack/bert-base-uncased-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-imdb") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-imdb") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5525053dc6b69d90a5939024dd9d50050dcbb38e99eca027923a26540d5a7cd
- Size of remote file:
- 438 MB
- SHA256:
- 6cf58682775c7bea59ece37f54c0c9efbeafc6eafbe639c6a268e00fb83b997b
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