Text Generation
PEFT
Safetensors
English
lora
qwen2.5
qwen2.5-coder
code
reasoning
pedagogy
fine-tuned
conversational
Instructions to use mechramc/codek-qwen2.5-coder-7b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mechramc/codek-qwen2.5-coder-7b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Coder-7B-Instruct") model = PeftModel.from_pretrained(base_model, "mechramc/codek-qwen2.5-coder-7b-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e96dd4ae1d2df772ea3bbc942468b6f624624d437352f82360c528a3910b730
- Size of remote file:
- 11.4 MB
- SHA256:
- fab42efe8d17406525a9154b728cf9e957629a8ed7ce997770efdd71128c6a1a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.