Instructions to use CMU-AIR2/code-lora-hard-gh-mixture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CMU-AIR2/code-lora-hard-gh-mixture with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-1.3b-instruct") model = PeftModel.from_pretrained(base_model, "CMU-AIR2/code-lora-hard-gh-mixture") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from CMU-AIR2/code-lora-hard-gh-mixture: direct link, hf CLI and curl.
- Browser
- Download file 60.5 MB
-
https://huggingface.co/CMU-AIR2/code-lora-hard-gh-mixture/resolve/main/optimizer.pt
- Command line
-
hf download hf://CMU-AIR2/code-lora-hard-gh-mixture/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CMU-AIR2/code-lora-hard-gh-mixture/resolve/main/optimizer.pt
60.5 MB
- Xet hash:
- 84d9c8db0b5258f084de35a51614dd0be3c6885ce0c3236d5669673130e7808c
- Size of remote file:
- 60.5 MB
- SHA256:
- d611c340e44ffb28d62426aa8860899647ba50ba0e4539c8c093901bf438cb01
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