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:
- 6b77b281e4f057727c773a8659761394767aac6f92d5374ca924b5ce667be78f
- Size of remote file:
- 6.56 MB
- SHA256:
- d4a1d7c8d8c75cd6435ae871875e399eb301c916fa8a7035e53d9903fac5b3dd
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