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
Upload rng_state.pth with git-lfs
Browse files- rng_state.pth +3 -0
rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:6ce04baaf5e631e1a7857e328a77f81db6f1182144409c62011a8ff074883f64
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size 14503
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