Instructions to use binwang/RSE-RoBERTa-base-10-relations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binwang/RSE-RoBERTa-base-10-relations with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RoBERTaForRSE tokenizer = AutoTokenizer.from_pretrained("binwang/RSE-RoBERTa-base-10-relations") model = RoBERTaForRSE.from_pretrained("binwang/RSE-RoBERTa-base-10-relations", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from binwang/RSE-RoBERTa-base-10-relations: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/binwang/RSE-RoBERTa-base-10-relations/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://binwang/RSE-RoBERTa-base-10-relations/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/binwang/RSE-RoBERTa-base-10-relations/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 4171285b3cc0cdb7b40a52dcddc52e262d40d857010644ff301019f56f6e7f78
- Size of remote file:
- 499 MB
- SHA256:
- 671ac6690e476dcbd743d31b3d37313b8c06b7f254afcfdf87e57e57e6d5b8ba
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