Instructions to use lvwerra/bert-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lvwerra/bert-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lvwerra/bert-imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lvwerra/bert-imdb") model = AutoModelForSequenceClassification.from_pretrained("lvwerra/bert-imdb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3684c54dd34bc91bba8c37bcb52459959438de4e3c1e15a54467bc6bc6991116
- Size of remote file:
- 1.33 GB
- SHA256:
- eb300a0ac9fdf3b487e43977afa1f56e201c43bc8aae3d63ee5c1e1ad214367b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.