Instructions to use gpol13/codet5_qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gpol13/codet5_qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("Salesforce/codet5-base") model = PeftModel.from_pretrained(base_model, "gpol13/codet5_qlora") - Transformers
How to use gpol13/codet5_qlora with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("gpol13/codet5_qlora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-9213/training_args.bin from gpol13/codet5_qlora: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/gpol13/codet5_qlora/resolve/main/checkpoint-9213/training_args.bin
- Command line
-
hf download hf://gpol13/codet5_qlora/checkpoint-9213/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gpol13/codet5_qlora/resolve/main/checkpoint-9213/training_args.bin
4.92 kB
- Xet hash:
- f45ce5c5aa5631c84d4760d074f4ddd9ec1fb9a87f772105d0a188ea7ef106b5
- Size of remote file:
- 4.92 kB
- SHA256:
- 21e7988a724f50ab4d65854a8bd4de7b4eceb713886a6a05ceeaeae7fb11b713
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