Instructions to use BigSalmon/Rowerta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/Rowerta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BigSalmon/Rowerta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/Rowerta") model = AutoModelForMaskedLM.from_pretrained("BigSalmon/Rowerta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BigSalmon/Rowerta: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/BigSalmon/Rowerta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://BigSalmon/Rowerta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BigSalmon/Rowerta/resolve/main/pytorch_model.bin
329 MB
- Xet hash:
- d20af3577a996798ed85e6a0c254194c868198586fbc6674c7c48da721ed1da5
- Size of remote file:
- 329 MB
- SHA256:
- a9fcb13d6d30bdf02afbfee4bca50cd308f98ce4ebd4d02cd585efed37488288
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