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:
- ef887457871af627312c47cd4159760ece81afb6bec7155c2acbb17c152e4bd6
- Size of remote file:
- 6.6 MB
- SHA256:
- d9f78c929827a677153a897227e9b3ad3ea905722e7c0928e885823d129a5561
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