Instructions to use hf-tiny-model-private/tiny-random-PegasusXModel 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-PegasusXModel 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-PegasusXModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-PegasusXModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-PegasusXModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 262ddddfb1af468a005c5339e8b50336102cb2c107bb05278e6140c15e27e408
- Size of remote file:
- 6.19 MB
- SHA256:
- cb367b58c511e121b20a94bd5e105e047592e4c711b1fd049f792536702986c3
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