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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bc8465be03af3513e9693d364c9d79efa8ec86704d1240e3eefa32370b9981a
- Size of remote file:
- 499 MB
- SHA256:
- d738f7afc8033e380e243df7497056793e649d2d3c2aebcf8bc3462cde5406eb
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