Instructions to use sgugger/my-bert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/my-bert-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sgugger/my-bert-model", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sgugger/my-bert-model", trust_remote_code=True) model = AutoModel.from_pretrained("sgugger/my-bert-model", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1c45173a99b765d8d36841b629bed1d3a69cb0ee30c3bb02f998195e0fcaab5
- Size of remote file:
- 433 MB
- SHA256:
- 5924121a66d99ee2983de8025e32ce5378a98928719b916719d810dc07be30c4
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