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:
- fd3521c5afe6a02590bb1c9a3d36e87a36e4c3b1e9a7b0088cc119e7207c2f03
- Size of remote file:
- 4.47 MB
- SHA256:
- 63accc63e6ec7867fb462114e1f785898fe54d6ff38319c34e9c413a2dd67b56
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