Instructions to use DazMashaly/code_llama3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DazMashaly/code_llama3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-bnb-4bit") model = PeftModel.from_pretrained(base_model, "DazMashaly/code_llama3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c0236d0c3a233231d6405131a8303adbf18d5d59da51f71bc991242cf89ac32
- Size of remote file:
- 84.6 MB
- SHA256:
- 0d3b143de90fa504b45b3823c876200acfae976812be8d711dc8fb2703644d42
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