Instructions to use Syghmon/qwen3-4b-thinking-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Syghmon/qwen3-4b-thinking-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Syghmon/qwen3-4b-thinking-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76cdf2883065c6b3483bfdb5045848406313de4b914d12672e9991997fee8481
- Size of remote file:
- 6.23 kB
- SHA256:
- f8ec5ec5913b34d9ba43723ef69257146704f3940055602bcda7b9eab3df5c99
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.