Instructions to use hf-tiny-model-private/tiny-random-RoFormerModel 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-RoFormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-RoFormerModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b73de9c21cc5f3db21a89091302ba9da0026b0977bc3d44036c13a07a12d59c7
- Size of remote file:
- 6.67 MB
- SHA256:
- de46dab2588d49ded3f4fa22dc6f9dbaa540fd78af7bd00b41fad21673356386
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