Instructions to use hf-internal-testing/tiny-random-RoFormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RoFormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-RoFormerModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RoFormerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-RoFormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8351530d11a5bd738dd3298b71d662543a071b7a60aa08655c2fb55d83763748
- Size of remote file:
- 6.56 MB
- SHA256:
- 4b4ff2e07667b7b02830f29fbeca65fabbebdf86be711722118c719ede58045e
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