Instructions to use johnwee1/peft-starcoder-lora-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use johnwee1/peft-starcoder-lora-python with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoderbase-1b") model = PeftModel.from_pretrained(base_model, "johnwee1/peft-starcoder-lora-python") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from johnwee1/peft-starcoder-lora-python: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/johnwee1/peft-starcoder-lora-python/resolve/c13b92be2fb03b7b5a4af756dbd83a9aada013a6/training_args.bin
- Command line
-
hf download hf://johnwee1/peft-starcoder-lora-python@c13b92be2fb03b7b5a4af756dbd83a9aada013a6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/johnwee1/peft-starcoder-lora-python/resolve/c13b92be2fb03b7b5a4af756dbd83a9aada013a6/training_args.bin
5.11 kB
- Xet hash:
- 16c528c54f99b621f7e20176bd644787f208992fbf946e360d95e2234f09d461
- Size of remote file:
- 5.11 kB
- SHA256:
- edde6946fd3ea661830280b6392ec64661d079c9d2702d518717f53127fe0228
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