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/0af13bde8e4b012e992179e4afb418ff7a749f9a/training_args.bin
- Command line
-
hf download hf://johnwee1/peft-starcoder-lora-python@0af13bde8e4b012e992179e4afb418ff7a749f9a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/johnwee1/peft-starcoder-lora-python/resolve/0af13bde8e4b012e992179e4afb418ff7a749f9a/training_args.bin
5.11 kB
- Xet hash:
- bf4065f4c7ead5674ac425239d056b4b06ea69390e6d59450bb00034bd8ec140
- Size of remote file:
- 5.11 kB
- SHA256:
- 12477b9fc7dcd444d6c2fda7ae9b79f5a63fc166d361f213d69f5ef7e4685bd2
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