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:
- 17bcbd4a246f21bccefc85aaafa4368a20c9652ec29be3a946c41d42219bdc74
- Size of remote file:
- 4.42 MB
- SHA256:
- 8470851884db14ad1df1fd126362d45fe12cc421f1a0166829cfe61cdf77d93a
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