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 rng_state.pth from Rustem/distilroberta-base-trained: direct link, hf CLI and curl.
- Browser
- Download file 14.5 kB
-
https://huggingface.co/Rustem/distilroberta-base-trained/resolve/main/rng_state.pth
- Command line
-
hf download hf://Rustem/distilroberta-base-trained/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/Rustem/distilroberta-base-trained/resolve/main/rng_state.pth
14.5 kB
- Xet hash:
- 906462e4f783dc0c2578f85169d2529b4c314da15df059a4ac52cea772ec9d6e
- Size of remote file:
- 14.5 kB
- SHA256:
- af7c4988ce37692ec7705ecb2041a7aad0df486827d5850a6b90a00a6d28476e
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