Instructions to use hf-internal-testing/tiny-random-PegasusXForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PegasusXForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PegasusXForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-PegasusXForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b6f283c334d8a848b6073122aa19f4359e1cb2f089af7b0d0e45501bbfcb93d
- Size of remote file:
- 6.19 MB
- SHA256:
- 6969ed72ff66ae054ada192cdc75b68ed8b6d361fa5d3f006c914919e398fa0b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.