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:
- 8ae873fa84f15b7c81649c89da36afb3984556415ac7f539b7e8763fddd2218b
- Size of remote file:
- 4.47 MB
- SHA256:
- dbb099d5bfd33e76a37f356b0e0b8b57a22b8755daf6cddcd161c504d8f5211d
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