Instructions to use Rustem/distilroberta-base-trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rustem/distilroberta-base-trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rustem/distilroberta-base-trained")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rustem/distilroberta-base-trained") model = AutoModelForMaskedLM.from_pretrained("Rustem/distilroberta-base-trained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Rustem/distilroberta-base-trained: direct link, hf CLI and curl.
- Browser
- Download file 657 MB
-
https://huggingface.co/Rustem/distilroberta-base-trained/resolve/main/optimizer.pt
- Command line
-
hf download hf://Rustem/distilroberta-base-trained/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Rustem/distilroberta-base-trained/resolve/main/optimizer.pt
657 MB
- Xet hash:
- 764fcd3d8d6294b5f897aa353b5319a02bd03e658bc6a67990f20449cad753e7
- Size of remote file:
- 657 MB
- SHA256:
- 0caa4d63a5b77e1f0f30a355b283120566ff87bef654ecc42762cf4862a540d2
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