Instructions to use moos124/qwen-2.5-coder-3b-lora-reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moos124/qwen-2.5-coder-3b-lora-reasoning with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("moos124/qwen-2.5-coder-3b-lora-reasoning", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3adef1ad7a716c4061a0dcacbb07c51e4756c2f9256f220af44c84e7e7dcf920
- Size of remote file:
- 5.78 kB
- SHA256:
- 3401f82e63562390f02240c098ee049113e00de67975d136b844c74f4d3c9f71
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.