Instructions to use bertin-project/bertin-roberta-base-spanish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertin-project/bertin-roberta-base-spanish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bertin-project/bertin-roberta-base-spanish")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-roberta-base-spanish") model = AutoModelForMaskedLM.from_pretrained("bertin-project/bertin-roberta-base-spanish", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bertin-project/bertin-roberta-base-spanish: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/v1-512/pytorch_model.bin
- Command line
-
hf download hf://bertin-project/bertin-roberta-base-spanish@v1-512/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/v1-512/pytorch_model.bin
499 MB
- Xet hash:
- 551fe41de1c1760aeb3916e63a8f25c1c68963ea845128c89004d12465b7cf7b
- Size of remote file:
- 499 MB
- SHA256:
- 76381a0424ff057832e334d58db107b8f41d71a277888c98f44e23f011007b97
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