Instructions to use g8a9/roberta-tiny-8l-10M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use g8a9/roberta-tiny-8l-10M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="g8a9/roberta-tiny-8l-10M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("g8a9/roberta-tiny-8l-10M") model = AutoModelForMaskedLM.from_pretrained("g8a9/roberta-tiny-8l-10M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 241d0179a050fe4a8b2390f70c0d104e590b819ead189a72f43cec32623879a4
- Size of remote file:
- 3.5 kB
- SHA256:
- fcb8ba5323e093674b45fde3d7a10801b62f8db7bd13eed458e75565e3ced275
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