Instructions to use afrias5/codellama-7b-Python-Score4096V2-45 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use afrias5/codellama-7b-Python-Score4096V2-45 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-Score4096V2-45") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3dab70878237440eea2775b905b7e815e5fc08bb634ab8b4f126be7edaa0429
- Size of remote file:
- 1.61 GB
- SHA256:
- 486fcbf3b426d5ee9ac6c41ac7ade390b29fcd8f07c306b57eb6306f15fd181d
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