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:
- 3755c2aa719088423876a8e20c282d0a3040c62ee5747f08d8760d63fddddbf5
- Size of remote file:
- 6.19 MB
- SHA256:
- b5ccd44789dbb358e39ce712e49bb858b23ba4f14fe89a82e5b80ed41d4d17f6
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