Instructions to use ZiHDeng/peft-lora-starcoder1B-Instruction-ny8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ZiHDeng/peft-lora-starcoder1B-Instruction-ny8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoderbase-1b") model = PeftModel.from_pretrained(base_model, "ZiHDeng/peft-lora-starcoder1B-Instruction-ny8") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ZiHDeng/peft-lora-starcoder1B-Instruction-ny8: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/ZiHDeng/peft-lora-starcoder1B-Instruction-ny8/resolve/main/training_args.bin
- Command line
-
hf download hf://ZiHDeng/peft-lora-starcoder1B-Instruction-ny8/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ZiHDeng/peft-lora-starcoder1B-Instruction-ny8/resolve/main/training_args.bin
4.79 kB
- Xet hash:
- 2827617de1415ee2a513f4d07b3031fb59cc6ada033574d9d04954d019b29a1f
- Size of remote file:
- 4.79 kB
- SHA256:
- f0f2bfb80ba78163661e729c7d0e0436aa79c2259902714e30655063c8e883df
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