Instructions to use kazma1/simcse-robertaLarge-matching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kazma1/simcse-robertaLarge-matching with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RobertaForCL tokenizer = AutoTokenizer.from_pretrained("kazma1/simcse-robertaLarge-matching") model = RobertaForCL.from_pretrained("kazma1/simcse-robertaLarge-matching", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kazma1/simcse-robertaLarge-matching: direct link, hf CLI and curl.
- Browser
- Download file 271 MB
-
https://huggingface.co/kazma1/simcse-robertaLarge-matching/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kazma1/simcse-robertaLarge-matching/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kazma1/simcse-robertaLarge-matching/resolve/main/pytorch_model.bin
271 MB
- Xet hash:
- fb0c4b45ab96e205d0dac73c8e1d8af2b4ceaf6b5972cb5c667c26c6e5d4ac4e
- Size of remote file:
- 271 MB
- SHA256:
- 5daff0c024a57bede1ae3a8deae9c231e61e255052299c7cc5f314f33a6af526
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