Instructions to use nandezgarcia/roberta-base-bne-finetuned-recores with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nandezgarcia/roberta-base-bne-finetuned-recores with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("nandezgarcia/roberta-base-bne-finetuned-recores") model = AutoModelForMultipleChoice.from_pretrained("nandezgarcia/roberta-base-bne-finetuned-recores", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nandezgarcia/roberta-base-bne-finetuned-recores: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/nandezgarcia/roberta-base-bne-finetuned-recores/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nandezgarcia/roberta-base-bne-finetuned-recores/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nandezgarcia/roberta-base-bne-finetuned-recores/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 7a13bc3a50a08ee654ae749b0b281e59ba4e8d38399491ffd3cbfc7d263fa40b
- Size of remote file:
- 499 MB
- SHA256:
- c17045c0befee40eb4969c56e9db91daa3651cf8ad71c2d5ec1efdd6303b75d7
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