Instructions to use hf-internal-testing/tiny-random-LongT5ForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LongT5ForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LongT5ForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-LongT5ForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62157d04345bee3321ce9486e4bf321b0e9ea8537baefd964948764b2d25ee49
- Size of remote file:
- 4.62 MB
- SHA256:
- c0e9bccfa47d83ae0163a21f81e2faabb16bc85bd35a5dfc3bbddbc644e49834
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