Instructions to use hf-tiny-model-private/tiny-random-PegasusXForConditionalGeneration 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-PegasusXForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-PegasusXForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-PegasusXForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 505b2f45ede0453525832e692c93bddd3c887dde52b4810a6345d5a17e2d71be
- Size of remote file:
- 6.2 MB
- SHA256:
- 84eb72278319348a453e46dd82a00e73133cf2ccbbe82de299f5e3c338079e2d
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