Instructions to use g8a9/roberta-tiny-4l-10M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use g8a9/roberta-tiny-4l-10M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="g8a9/roberta-tiny-4l-10M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("g8a9/roberta-tiny-4l-10M") model = AutoModelForMaskedLM.from_pretrained("g8a9/roberta-tiny-4l-10M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c40f32c1abffcf06abcc858126dbb980165566138b24a9f907e7b45f80a264c
- Size of remote file:
- 380 MB
- SHA256:
- 16cdafd0882dbe90e638c6dd7e7a4b9ee3cb0a454c38c8b9e15c2781febdbdc3
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