Instructions to use hf-tiny-model-private/tiny-random-T5ForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-T5ForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-T5ForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-T5ForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8cc6d72c2d4028cc2b9fb7e4583beac69353f6bc8f9ee069d56cce3e1233aada
- Size of remote file:
- 12.9 MB
- SHA256:
- db6e12ee2319dc97e4e809518b2e195d03df5c9820c39c2f737209769ff7a45c
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