Instructions to use jfernandez/cebfil-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jfernandez/cebfil-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jfernandez/cebfil-roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jfernandez/cebfil-roberta") model = AutoModelForMaskedLM.from_pretrained("jfernandez/cebfil-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jfernandez/cebfil-roberta: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/jfernandez/cebfil-roberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jfernandez/cebfil-roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jfernandez/cebfil-roberta/resolve/main/pytorch_model.bin
504 MB
- Xet hash:
- dfae9710dafe4c01d7cbdfcce38df4db92edea5952db843c23f85c2aeb185e8e
- Size of remote file:
- 504 MB
- SHA256:
- c2fc345511011df68f4d14a799a9ef40bf66950886afab2a68c31c4e67cb1d44
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