Instructions to use longcld/t5-small-e2e-qa-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use longcld/t5-small-e2e-qa-full with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("longcld/t5-small-e2e-qa-full") model = AutoModelForSeq2SeqLM.from_pretrained("longcld/t5-small-e2e-qa-full", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from longcld/t5-small-e2e-qa-full: direct link, hf CLI and curl.
- Browser
- Download file 688 MB
-
https://huggingface.co/longcld/t5-small-e2e-qa-full/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://longcld/t5-small-e2e-qa-full/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/longcld/t5-small-e2e-qa-full/resolve/main/pytorch_model.bin
688 MB
- Xet hash:
- 4f9a667a8885ac829a7ac5e82482d48e5a51939256634801cd9aa34c4d0daa6e
- Size of remote file:
- 688 MB
- SHA256:
- 4af008a4fb55ce22292b6d47f4f921949c51109b77f9094d3ec89f3c9810fcac
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