Instructions to use osunlp/ReasonBERT-BERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osunlp/ReasonBERT-BERT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="osunlp/ReasonBERT-BERT-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("osunlp/ReasonBERT-BERT-base") model = AutoModel.from_pretrained("osunlp/ReasonBERT-BERT-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a13e83e436277d098dfa46d233197e3a61c53bc15668f8f0182f39e7fe7eff67
- Size of remote file:
- 438 MB
- SHA256:
- ba080089ae7b79666151dd62cac4fc4c34d9773427822d0dc0d607ba9e58631e
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