Instructions to use distilbert/distilroberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distilbert/distilroberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="distilbert/distilroberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("distilbert/distilroberta-base") model = AutoModelForMaskedLM.from_pretrained("distilbert/distilroberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.safetensors from distilbert/distilroberta-base: direct link, hf CLI and curl.
- Browser
- Download file 331 MB
-
https://huggingface.co/distilbert/distilroberta-base/resolve/main/model.safetensors
- Command line
-
hf download hf://distilbert/distilroberta-base/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/distilbert/distilroberta-base/resolve/main/model.safetensors
331 MB
- Xet hash:
- 1682c5692768e19ad63ad725ef5b77939078f2f46d3c3738bbbd5068cb53cfef
- Size of remote file:
- 331 MB
- SHA256:
- 2b11ca9cf3d2cbb44cc1a93ad96aedc2894231ae6e33e2d2268c3d7b1ff97663
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