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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af62e0b206c0ba31fb06a963cf61e84b9b580f1116167d79e95f3834ca2656f2
- Size of remote file:
- 6.22 MB
- SHA256:
- 3879801b86581953cd9fd295d6ca1a24ffa57b6e3877a9767a77fc2952c54494
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