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 tokenizer/preprocessor_config.json from original repo
Browse files
tokenizer/preprocessor_config.json
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{
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"min_pixels": 3136,
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"max_pixels": 12845056,
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"patch_size": 14,
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"temporal_patch_size": 2,
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"merge_size": 2,
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"image_processor_type": "Qwen2VLImageProcessor",
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"processor_class": "Qwen2_5_VLProcessor"
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}
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