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:
- 6cc576dceb3dd2308a80def903b9490bda41b2aa22b52f1dcf7a13fabff0230b
- Size of remote file:
- 688 MB
- SHA256:
- f9f02989a9ec6ef92d1f9d7a4083c69c59e574acbc98f6fc53963490f8bc7884
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.