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:
- 43f4a8f8afcfc9c4b23ea76293cfea2293763dcf15f21ea324151cf59925d261
- Size of remote file:
- 6.62 MB
- SHA256:
- 11690dbbc9ce0791b90811d92e5b6f914c6bf52c1021e46b0aeb61a55b36efa2
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