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 optimizer.pt from Kartik305/starcoderbase-smol-python-lora: direct link, hf CLI and curl.
- Browser
- Download file 35.9 MB
-
https://huggingface.co/Kartik305/starcoderbase-smol-python-lora/resolve/main/optimizer.pt
- Command line
-
hf download hf://Kartik305/starcoderbase-smol-python-lora/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Kartik305/starcoderbase-smol-python-lora/resolve/main/optimizer.pt
35.9 MB
- Xet hash:
- 50055a16fc89af757de23bf5fffd551d0af3abe67282ae49ebccf25f9cf3eba6
- Size of remote file:
- 35.9 MB
- SHA256:
- 4c8a1aa733479e4dd46a83af1b2c88c7eaf4d3dc4b0549afb450ad3a8374022c
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