Instructions to use binwang/RSE-RoBERTa-large-STS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binwang/RSE-RoBERTa-large-STS with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RoBERTaForRSE tokenizer = AutoTokenizer.from_pretrained("binwang/RSE-RoBERTa-large-STS") model = RoBERTaForRSE.from_pretrained("binwang/RSE-RoBERTa-large-STS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from binwang/RSE-RoBERTa-large-STS: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/binwang/RSE-RoBERTa-large-STS/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://binwang/RSE-RoBERTa-large-STS/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/binwang/RSE-RoBERTa-large-STS/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 04373c03689f06e797a20cbbf8861830a528bff3720f293baf8fca583c98c0f2
- Size of remote file:
- 1.42 GB
- SHA256:
- 7c786c3aea021f3a5109eac52f3459db97060ace99723b7780dfda51e7d39496
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