Instructions to use hf-tiny-model-private/tiny-random-PegasusForConditionalGeneration 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-PegasusForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-PegasusForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-PegasusForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da4baa39c23776a9d2e2e393757ea1e4c71f4b2e3a88c5077d49f1546f108c01
- Size of remote file:
- 6.7 MB
- SHA256:
- 882ada92793fbc72a59527fe5e727740aa3723f2a4b5d4d54a862d9c072119e1
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