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:
- d99e987426970e7c31c0e8043c8fb8c88f546c08510384920f6250fd1fdcd52e
- Size of remote file:
- 6.31 MB
- SHA256:
- 1a5ab87b5fc4737aed1e04fafa7a75e6ed0a1021024a25b7c434198d69c1c55e
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