Instructions to use Anonymous/ReasonBERT-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anonymous/ReasonBERT-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Anonymous/ReasonBERT-BERT")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Anonymous/ReasonBERT-BERT") model = AutoModel.from_pretrained("Anonymous/ReasonBERT-BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c040436dc0d1615d1b96e919e9bdaca057b1647ae9427a7650077cfc3caa02a9
- Size of remote file:
- 438 MB
- SHA256:
- 05445b4de52e8031b27c2e5617646367c7f88eb626d3e6b4c0cae29cadb6ec3b
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