Instructions to use osunlp/ReasonBERT-TAPAS-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osunlp/ReasonBERT-TAPAS-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="osunlp/ReasonBERT-TAPAS-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("osunlp/ReasonBERT-TAPAS-base") model = AutoModel.from_pretrained("osunlp/ReasonBERT-TAPAS-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2222370be2f6a23b59c7216f34fdebd85bc53ce4f784d4083012d3997a0d38d
- Size of remote file:
- 443 MB
- SHA256:
- dcbbd308c4ef45627ffc3c7e7ca98c4844a8f7da8e4ada2c7224b9bcb3c7e6dc
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