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:
- 22141f6675236615651be26cf26e7d508d18bf6cf23781c06c16d9afcb53616b
- Size of remote file:
- 6.16 kB
- SHA256:
- df27ef39cb685558e10ac82c7ec97046f7eb2b73f1c95033cffac29272c029d2
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