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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8014bddd992a03cd8b40e52abf9e0894f5416ccbeff9f398301b684dc48ef726
- Size of remote file:
- 4.47 MB
- SHA256:
- f649ce28222de168c8efea50bf1c7658bb14a6e02116074a68d28fa88c062f2a
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