Instructions to use saadamin2k13/byT5_ft_semantic_parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saadamin2k13/byT5_ft_semantic_parser with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("saadamin2k13/byT5_ft_semantic_parser") model = AutoModelForSeq2SeqLM.from_pretrained("saadamin2k13/byT5_ft_semantic_parser", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from saadamin2k13/byT5_ft_semantic_parser: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/saadamin2k13/byT5_ft_semantic_parser/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://saadamin2k13/byT5_ft_semantic_parser/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/saadamin2k13/byT5_ft_semantic_parser/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- 8ea29e269c42c7adb90e3bab95089105dcbe01ba647ac457b4e50d37cb39ceb2
- Size of remote file:
- 2.33 GB
- SHA256:
- 23d4f5acbb23a4c7d844977318b722bdcfe8de0f54f08c695de1dabf33afd926
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