Instructions to use hauson-fan/RagRetriever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hauson-fan/RagRetriever with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RagRetriever tokenizer = AutoTokenizer.from_pretrained("hauson-fan/RagRetriever") model = RagRetriever.from_pretrained("hauson-fan/RagRetriever", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download question_encoder_tokenizer/tokenizer_config.json from hauson-fan/RagRetriever: direct link, hf CLI and curl.
- Browser
- Download file 48 Bytes
-
https://huggingface.co/hauson-fan/RagRetriever/resolve/main/question_encoder_tokenizer/tokenizer_config.json
- Command line
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hf download hf://hauson-fan/RagRetriever/question_encoder_tokenizer/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/hauson-fan/RagRetriever/resolve/main/question_encoder_tokenizer/tokenizer_config.json
48 Bytes
| {"do_lower_case": true, "model_max_length": 512} |