Instructions to use mehmetdavut/ruby3.4-qwen2.5-coder-1.5b-5k-hq-16bit-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-1.5b-5k-hq-16bit-gemini with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "mehmetdavut/ruby3.4-qwen2.5-coder-1.5b-5k-hq-16bit-gemini") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1677151a83ada08c046a327a4fc0a5731557aad40ea9b14be64b3fa88eb41f4f
- Size of remote file:
- 5.5 kB
- SHA256:
- 21e4c5bae53fbbff205204667fe062f542f60a510b63e5201612ea89fef0558f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.