Instructions to use longcld/t5-small-e2e-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use longcld/t5-small-e2e-qa with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("longcld/t5-small-e2e-qa") model = AutoModelForSeq2SeqLM.from_pretrained("longcld/t5-small-e2e-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 551089a2adf6aa122038854ca969f56aaade3bc80c8fbbfba78f3f14d19a42dc
- Size of remote file:
- 353 MB
- SHA256:
- 74f1a1606eaccc38d548088e90223e9960163001a8bc8a545385918255fac95b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.