Instructions to use EEsu/codeT5-adam-trial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EEsu/codeT5-adam-trial with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("EEsu/codeT5-adam-trial") model = AutoModelForSeq2SeqLM.from_pretrained("EEsu/codeT5-adam-trial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from EEsu/codeT5-adam-trial: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/EEsu/codeT5-adam-trial/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://EEsu/codeT5-adam-trial/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/EEsu/codeT5-adam-trial/resolve/main/last-checkpoint/training_args.bin
5.11 kB
- Xet hash:
- 5a5f114fc35f0e51acb8c570cb7f7750e0e99b5cd861012cf8cc7913a93b4d92
- Size of remote file:
- 5.11 kB
- SHA256:
- 1df71517f4dc470d2f3cdb8a3dc02bd9e727e7e19666a0a79aeb3afa58f1118e
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