Instructions to use leaf0788/structeval-qwen3-4b-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leaf0788/structeval-qwen3-4b-sft with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("leaf0788/structeval-qwen3-4b-sft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a1d9a548938f3d35920b87587c9dd32646c1e2db022ad2cc7dde3b2be62cb50
- Size of remote file:
- 11.4 MB
- SHA256:
- 6adb90dd2c38b281238c0f606f444f129358c61dc015dd772cf77654df557cee
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.