Instructions to use ramonzaca/roberto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ramonzaca/roberto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ramonzaca/roberto")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ramonzaca/roberto") model = AutoModelForMaskedLM.from_pretrained("ramonzaca/roberto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from ramonzaca/roberto: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/ramonzaca/roberto/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://ramonzaca/roberto@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/ramonzaca/roberto/resolve/refs%2Fpr%2F1/flax_model.msgpack
504 MB
- Xet hash:
- d10ef3089bdc453ef7c4f412f425f0e85264b415047b1a9d8652719927e88930
- Size of remote file:
- 504 MB
- SHA256:
- 9ad7ccd70a51e0709ebb93df5c4875ab033cf1310e7ba19eb4531fb7e8b60abe
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