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:
- f8fd7f3ada381ce32dafc6b472ad9a5e6849d3f024e1226fe2ee4259523cbf66
- Size of remote file:
- 1.61 GB
- SHA256:
- f288291374f04e21b38a2b75ecead5b68d6cc8b6a04b275aa622b100cf0dcf81
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