Instructions to use Rustem/roberta-base-trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rustem/roberta-base-trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rustem/roberta-base-trained")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rustem/roberta-base-trained") model = AutoModelForMaskedLM.from_pretrained("Rustem/roberta-base-trained") - Notebooks
- Google Colab
- Kaggle
Upload optimizer.pt with git-lfs
Browse files- optimizer.pt +3 -0
optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:ef8155c5dfe2414b151a8233b8f70da9af63d17de657bb36d48fe7fa54d99836
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size 997696473
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