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:
- 0563a499fa8a30b2aae327b78fff01cf15956984d97db859a88091a13920e6b9
- Size of remote file:
- 380 MB
- SHA256:
- d02af1f1dbb54b42fb59137de2a28120000b828c76e2c72929ce85c9cf2e6b92
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