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:
- 09dac9cdba84ed5b2864ef02c9c8ca17b234215b51f17f5170c3525a7cadef3b
- Size of remote file:
- 27.4 MB
- SHA256:
- ba385d3d6405d26b6d22fe59abdf2e88257fd28c8883503b885581966fc60ef0
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