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:
- cb4bd166f2171afc8f2b415683ca4007a0cf2978e960ff635ef98ba29c5b2e8e
- Size of remote file:
- 3.5 kB
- SHA256:
- bd587968044bf454825342ab6290d516e6bc091b304465e93532653578051cb9
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