Instructions to use Master-AI-Lab/Lumi-Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Master-AI-Lab/Lumi-Transformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Master-AI-Lab/Lumi-Transformer") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Master-AI-Lab/Lumi-Transformer", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 184 Bytes
aff2585 | 1 2 3 4 5 6 7 8 9 10 11 | python==3.7.16 torch==1.9.0+cu111 torchvision==0.10.0+cu111 cudatoolkit==10.2.89 cuda==12.1.1 timm==0.4.12 opencv-python==4.4.0.46 termcolor==1.1.0 yacs==0.1.8 pyyaml==6.0 scipy==1.7.3 |