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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 906c3edee0b16307f70d38c89b30490289c605642750a7faca3ae26cf93e7d17
- Size of remote file:
- 6.2 MB
- SHA256:
- 4f7160e8bb73623c63e13fe2398a1281a2e9bb58cd4910d2bf5d87afc79be32c
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