Instructions to use g8a9/roberta-tiny-10M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use g8a9/roberta-tiny-10M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="g8a9/roberta-tiny-10M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("g8a9/roberta-tiny-10M") model = AutoModelForMaskedLM.from_pretrained("g8a9/roberta-tiny-10M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9307dbc1f5c1fbc8f6807687bbb714305eeb49ae4aeefd15614b4b2241952ef6
- Size of remote file:
- 3.5 kB
- SHA256:
- a554cfbb97467f4b15be7f79c1c2ce3b4bc1fcf7e924cc7468efcd250919f2f1
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