Instructions to use afrias5/codellama-7b-Python-Score4096V2-81 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use afrias5/codellama-7b-Python-Score4096V2-81 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/CodeLlama-7b-Python-hf") model = PeftModel.from_pretrained(base_model, "afrias5/codellama-7b-Python-Score4096V2-81") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 225492f998f178f15bdd4e80b15f9d966c59227ce421843cca11006b20c727c4
- Size of remote file:
- 6.33 kB
- SHA256:
- 1667983036846ee79d983f227caa1d8aa9548fb9c191913987340907a3be2aef
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