Instructions to use CMU-AIR2/code-lora-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CMU-AIR2/code-lora-simple 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-simple") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from CMU-AIR2/code-lora-simple: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/CMU-AIR2/code-lora-simple/resolve/main/rng_state.pth
- Command line
-
hf download hf://CMU-AIR2/code-lora-simple/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/CMU-AIR2/code-lora-simple/resolve/main/rng_state.pth
14.2 kB
- Xet hash:
- 34c9448b683d1d2fb3728bf535be493e4113ce642ba50ede8bff89c52ddb3262
- Size of remote file:
- 14.2 kB
- SHA256:
- 802325e51b7945f8a2513d9d90e2dbd79551b82a264561114d1b3acde0ec378a
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