Instructions to use Tomasz/roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tomasz/roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Tomasz/roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Tomasz/roberta") model = AutoModelForMaskedLM.from_pretrained("Tomasz/roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Tomasz/roberta: direct link, hf CLI and curl.
- Browser
- Download file 1.43 GB
-
https://huggingface.co/Tomasz/roberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Tomasz/roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Tomasz/roberta/resolve/main/pytorch_model.bin
1.43 GB
- Xet hash:
- 9043c9da4786d505884474d578d5086e74336622178518d930676d268416a9e5
- Size of remote file:
- 1.43 GB
- SHA256:
- f331e86558ef82ac3ac8df8c045fd7f4cc885bb4aafe3474eeacf22c807f3e51
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