Instructions to use patrickvonplaten/rag-sequence-ques-enc-prev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickvonplaten/rag-sequence-ques-enc-prev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="patrickvonplaten/rag-sequence-ques-enc-prev")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("patrickvonplaten/rag-sequence-ques-enc-prev") model = AutoModel.from_pretrained("patrickvonplaten/rag-sequence-ques-enc-prev") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87cb8a3b3155a2dede78f5b3edd843eef68867b603eecce648a6828cda39e3d1
- Size of remote file:
- 438 MB
- SHA256:
- 918713978cbd98b4b3087040c779dbeb228f5fa8fcf6e3ff25763e59dad9ffb3
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