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
clone scheduler/scheduler_config.json
Browse files
scheduler/scheduler_config.json
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{
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"_class_name": "FlowMatchEulerDiscreteScheduler",
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"_diffusers_version": "0.30.0.dev0",
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"base_image_seq_len": 256,
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"base_shift": 1.15,
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"max_image_seq_len": 4096,
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"max_shift": 1.15,
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"num_train_timesteps": 1000,
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"shift": 1.0,
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"use_dynamic_shifting": true
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}
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