Instructions to use rootlocalghost/LongCat-Image-Edit-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rootlocalghost/LongCat-Image-Edit-Turbo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="rootlocalghost/LongCat-Image-Edit-Turbo")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rootlocalghost/LongCat-Image-Edit-Turbo", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "LongCatImageTransformer2DModel", | |
| "_diffusers_version": "0.30.0.dev0", | |
| "attention_head_dim": 128, | |
| "in_channels": 64, | |
| "joint_attention_dim": 3584, | |
| "num_attention_heads": 24, | |
| "num_layers": 10, | |
| "num_single_layers": 20, | |
| "patch_size": 1, | |
| "pooled_projection_dim": 3584 | |
| } | |