Instructions to use peft-internal-testing/tiny-random-T5ForConditionalGeneration-calibrated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peft-internal-testing/tiny-random-T5ForConditionalGeneration-calibrated with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("peft-internal-testing/tiny-random-T5ForConditionalGeneration-calibrated") model = AutoModelForSeq2SeqLM.from_pretrained("peft-internal-testing/tiny-random-T5ForConditionalGeneration-calibrated") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 095820f9ace31aa048646378b822d2dd9cc6500a6075ebe656bbc372dfde89ee
- Size of remote file:
- 4.47 MB
- SHA256:
- dcaabc165a9168c70a4aeaf2734fadde067975d9630e3b6a36b314f263b8f4f4
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