Instructions to use rootlocalghost/LongCat-Image-Edit-Turbo-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rootlocalghost/LongCat-Image-Edit-Turbo-FP8 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-FP8")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rootlocalghost/LongCat-Image-Edit-Turbo-FP8", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Copy model_index.json from original repo
Browse files- model_index.json +28 -0
model_index.json
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{
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"_class_name": "LongCatImageEditPipeline",
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"_diffusers_version": "0.35.1",
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"scheduler": [
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"diffusers",
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"FlowMatchEulerDiscreteScheduler"
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],
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"text_encoder": [
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"transformers",
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"Qwen2_5_VLForConditionalGeneration"
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],
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"tokenizer": [
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"transformers",
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"Qwen2Tokenizer"
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],
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"text_processor": [
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"transformers",
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"Qwen2VLProcessor"
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],
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"transformer": [
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"diffusers",
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"LongCatImageTransformer2DModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKL"
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]
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}
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