Instructions to use eclat12450/fine-tuned-NSPbert-14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eclat12450/fine-tuned-NSPbert-14 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForNextSentencePrediction tokenizer = AutoTokenizer.from_pretrained("eclat12450/fine-tuned-NSPbert-14") model = AutoModelForNextSentencePrediction.from_pretrained("eclat12450/fine-tuned-NSPbert-14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eclat12450/fine-tuned-NSPbert-14: direct link, hf CLI and curl.
- Browser
- Download file 711 MB
-
https://huggingface.co/eclat12450/fine-tuned-NSPbert-14/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eclat12450/fine-tuned-NSPbert-14/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eclat12450/fine-tuned-NSPbert-14/resolve/main/pytorch_model.bin
711 MB
- Xet hash:
- dcfb62d0b4a59317584795ed2eca23d427fa2a8549ce5431f5765d4ca574df63
- Size of remote file:
- 711 MB
- SHA256:
- 0c49e3e7684932d57bc83d611351cff0154b4403f93d0527e46a19b460ae6cfe
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