Instructions to use mehmetdavut/ruby3.4-qwen2.5-coder-7b-5k-all-8bit-gemini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mehmetdavut/ruby3.4-qwen2.5-coder-7b-5k-all-8bit-gemini with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct") model = PeftModel.from_pretrained(base_model, "mehmetdavut/ruby3.4-qwen2.5-coder-7b-5k-all-8bit-gemini") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from mehmetdavut/ruby3.4-qwen2.5-coder-7b-5k-all-8bit-gemini: direct link, hf CLI and curl.
- Browser
- Download file 162 MB
-
https://huggingface.co/mehmetdavut/ruby3.4-qwen2.5-coder-7b-5k-all-8bit-gemini/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://mehmetdavut/ruby3.4-qwen2.5-coder-7b-5k-all-8bit-gemini/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/mehmetdavut/ruby3.4-qwen2.5-coder-7b-5k-all-8bit-gemini/resolve/main/adapter_model.safetensors
162 MB
- Xet hash:
- eccca83c1857b8b74b9b15d3c237392a66f22d059e27d70c74de06ef5f81d3c1
- Size of remote file:
- 162 MB
- SHA256:
- 25ee3dab3dd8e4372e9c8703eb50f43848464d26306ec4b34dfb3bf11e83f7d7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.