Instructions to use gpol13/codet5_sparse_lora_l1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gpol13/codet5_sparse_lora_l1 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_sparse_lora_l1") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gpol13/codet5_sparse_lora_l1: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/gpol13/codet5_sparse_lora_l1/resolve/main/training_args.bin
- Command line
-
hf download hf://gpol13/codet5_sparse_lora_l1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gpol13/codet5_sparse_lora_l1/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 4ec5bf6edc20c8959fe35a1f925945ba755f5ce9b2fd461f71c37a5dd837ca9f
- Size of remote file:
- 5.43 kB
- SHA256:
- 5603b8ad6e5c44098ff4d1375f09416bfc133ae607756a2e0d3c0084e202b93e
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