Instructions to use mlabonne/codellama-2-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mlabonne/codellama-2-7b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "mlabonne/codellama-2-7b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71ac3ccda4f7cbb3cdff4ec470dd15b764edaec13aae18456205500570556c73
- Size of remote file:
- 16.8 MB
- SHA256:
- bcf7eba5a15eb6358d1321cd8d25e073927c4def2a2ebbcd3235e999df7bf075
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