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:
- 8394e325eebc09cb9990dea4165bff4dd13761ffc7b22d4ca74200597c94fd20
- Size of remote file:
- 4.49 MB
- SHA256:
- 6328ce9c04b56c23615f68da489c1f1e4475c73e110beb191bda5ccd2481fa2a
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