Instructions to use scieditor/document-reranking-scibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scieditor/document-reranking-scibert with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForNextSentencePrediction tokenizer = AutoTokenizer.from_pretrained("scieditor/document-reranking-scibert") model = AutoModelForNextSentencePrediction.from_pretrained("scieditor/document-reranking-scibert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from scieditor/document-reranking-scibert: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/scieditor/document-reranking-scibert/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://scieditor/document-reranking-scibert@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/scieditor/document-reranking-scibert/resolve/refs%2Fpr%2F2/pytorch_model.bin
440 MB
- Xet hash:
- b9d579e149e91f09df02e83ac6b396822b9901a830b8aa250a6a3c59c6694f9a
- Size of remote file:
- 440 MB
- SHA256:
- b23390035a61e57bffda2e1b06e9c7e076e0ecfb2cfdaded006d83024520b7ea
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