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:
- 6a50a56c794b7f95be071862b7bb5c7b7bd0adc77d27abb9e90478857c2a0ed3
- Size of remote file:
- 6.23 MB
- SHA256:
- 944df95c1f81c888d7edd6b20eb88cc82f54d358a8333dc8316a782e1f6ac52c
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