Instructions to use nielsr/tapas-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nielsr/tapas-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nielsr/tapas-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nielsr/tapas-base") model = AutoModel.from_pretrained("nielsr/tapas-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90e2918a15dd47a08b3a2be7f3bc9e14fcd42f42ac8b352820ab1b525cda55ab
- Size of remote file:
- 443 MB
- SHA256:
- 61aef93d6fc89527ada14a47ec24284d6ae02376e64178213972e60a49152fc1
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