Instructions to use peft-internal-testing/tiny-random-t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peft-internal-testing/tiny-random-t5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("peft-internal-testing/tiny-random-t5") model = AutoModelForSeq2SeqLM.from_pretrained("peft-internal-testing/tiny-random-t5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22eacb28fa8d31dd3d3fdc5111b8b2048b106933de397b8988985e613cf05daa
- Size of remote file:
- 498 kB
- SHA256:
- 0e9630ace2c4c3f35fb3f99d9e30c8946ef3a649014afc21b7a4ea76737101cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.