Instructions to use hf-tiny-model-private/tiny-random-PegasusModel 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-PegasusModel 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-PegasusModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-PegasusModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-PegasusModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0457f1036c5bc6c24f5bdb1072a55800cb2864650175bfc2578f59ff5adb1277
- Size of remote file:
- 1.91 MB
- SHA256:
- 0015189ef36359283fec8b93cf6d9ce51bca37eb1101defc68a53b394913b96c
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