Instructions to use MustEr/rager with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MustEr/rager with Transformers:
# Load model directly from transformers import AutoTokenizer, RagSequenceForGeneration tokenizer = AutoTokenizer.from_pretrained("MustEr/rager") model = RagSequenceForGeneration.from_pretrained("MustEr/rager") - Notebooks
- Google Colab
- Kaggle
Rag model test
Browse files- config.json +4 -0
- pytorch_model.bin +3 -0
config.json
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{
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"index_name": "pytorch_model.bin",
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"index_path": "MustEr/gpt2-elite",
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7c5d3f4b8b76583b422fcb9189ad6c89d5d97a094541ce8932dce3ecabde1421
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size 548118077
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