Instructions to use hf-internal-testing/tiny-random-PegasusModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PegasusModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-PegasusModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PegasusModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PegasusModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 747b4dab7ff2f5b87d1fbe5232f20df09171ff566758d39f8be78b641ce80609
- Size of remote file:
- 6.31 MB
- SHA256:
- 0893af8a2472104c228d67d1537039e78db7c8e26780c55747afb707bd221387
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