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
File size: 326 Bytes
7eec2c5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"_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
}
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