Instructions to use lovepon/Meta-Llama-3-8B-code_alpaca-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lovepon/Meta-Llama-3-8B-code_alpaca-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/home/lizijian/Models/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "lovepon/Meta-Llama-3-8B-code_alpaca-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11973aac403ef9695af0ddf72a4bd0382b481a3549678513d859ab02e94c605b
- Size of remote file:
- 17.2 MB
- SHA256:
- 01e3be37353fbc0be479c7509d53c76860b7915a6b1852d5e75ec0c92707138b
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