Instructions to use Kartik305/starcoderbase-smol-python-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Kartik305/starcoderbase-smol-python-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoderbase") model = PeftModel.from_pretrained(base_model, "Kartik305/starcoderbase-smol-python-lora") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Kartik305/starcoderbase-smol-python-lora: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/Kartik305/starcoderbase-smol-python-lora/resolve/main/training_args.bin
- Command line
-
hf download hf://Kartik305/starcoderbase-smol-python-lora/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Kartik305/starcoderbase-smol-python-lora/resolve/main/training_args.bin
4.79 kB
- Xet hash:
- ea205cf34e7b218d5980bfbf066d97b48965be22a00acdf16070967d2a4a1c1e
- Size of remote file:
- 4.79 kB
- SHA256:
- 1ced839d97298f70ccb3ffec082fa5667508556fd1a217f38a6833b6e4c86063
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