Instructions to use mehmetdavut/ruby3.4-qwen2.5-coder-1.5b-1k-hq-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-1.5b-1k-hq-8bit-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-1k-hq-8bit-gemini") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5a457e6d397b7ae524a36215b79d04414f4215c1a389c040e18399d47df797f
- Size of remote file:
- 73.9 MB
- SHA256:
- b56f2595b754e8bd28d81223004614c46527c26f8af2a5dbe9e40ea633c39c9a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.