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:
# pip install -U transformers accelerate # 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
Download training_args.bin from longcld/t5-small-e2e-qa: direct link, hf CLI and curl.
- Browser
- Download file 2.61 kB
-
https://huggingface.co/longcld/t5-small-e2e-qa/resolve/main/training_args.bin
- Command line
-
hf download hf://longcld/t5-small-e2e-qa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/longcld/t5-small-e2e-qa/resolve/main/training_args.bin
2.61 kB
- Xet hash:
- 1aec2c6ae16fe9360fc3918c3d3257bc28a539105106f093087ec682c9e8c3d5
- Size of remote file:
- 2.61 kB
- SHA256:
- a8866efc220db599e3a3ed5db22928994cec12c97ba7ad4e862cf5bc62e056eb
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