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:
- 4f0bc1512b9a299046f67644999aa79cb62d661e057288127100118d7510b82b
- Size of remote file:
- 6.58 MB
- SHA256:
- 50c66457651e6356ec1e52cbf809ad7f73e5aa8eac806c8fb5ee5adc4be36d0f
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