Instructions to use hf-tiny-model-private/tiny-random-RoFormerForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-RoFormerForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-RoFormerForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a2605de4942518436acedf0689b970ed0ff93e8de26b51891b2e18dcc1079a1
- Size of remote file:
- 6.77 MB
- SHA256:
- 2265948b51bec7c71d4ded76a5b6a48d566305840c9bfb79d75a6f45a1fc2866
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