Instructions to use FacebookAI/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/roberta-base") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/roberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from FacebookAI/roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 501 MB
-
https://huggingface.co/FacebookAI/roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://FacebookAI/roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FacebookAI/roberta-base/resolve/main/pytorch_model.bin
501 MB
- Xet hash:
- 4c5bb8025a3a49d0fbfb9d103c0a05cb2182b0f206e115e078c3c160f0b7f8c7
- Size of remote file:
- 501 MB
- SHA256:
- 278b7a95739c4392fae9b818bb5343dde20be1b89318f37a6d939e1e1b9e461b
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