Type: huggingface.image_to_image.QwenImageEdit
Namespace: huggingface.image_to_image
Description
Performs image editing using the Qwen Image Edit model with support for GGUF quantization. image, editing, semantic, appearance, qwen, multimodal, quantization
Use cases:
- Semantic editing (object rotation, style transfer)
- Appearance editing (adding/removing elements)
- Precise text modifications in images
- Background and clothing changes
- Complex image transformations guided by text
- Memory-efficient editing using GGUF quantization
Properties
| Property | Type | Description | Default |
|---|---|---|---|
| model | hf.qwen_image_edit |
The Qwen-Image-Edit model to use for image editing. | {'type': 'hf.qwen_image_edit', 'repo_id': 'QuantStack/Qwen-Image-Edit-2509-GGUF', 'path': 'Qwen-Image-Edit-2509-Q4_K_M.gguf', 'variant': None, 'allow_patterns': None, 'ignore_patterns': None} |
| image | image |
The input image to edit | {'type': 'image', 'uri': '', 'asset_id': None, 'data': None} |
| prompt | str |
Text description of the desired edit to apply to the image | Change the object's color to blue |
| negative_prompt | str |
Text describing what should not appear in the edited image | `` |
| num_inference_steps | int |
Number of denoising steps for the editing process | 50 |
| true_cfg_scale | float |
Guidance scale for editing. Higher values follow the prompt more closely | 4.0 |
| seed | int |
Seed for the random number generator. Use -1 for a random seed | -1 |
| enable_memory_efficient_attention | bool |
Enable memory efficient attention to reduce VRAM usage. | True |
| enable_cpu_offload | bool |
Enable CPU offload to reduce VRAM usage. | True |
Outputs
| Output | Type | Description |
|---|---|---|
| output | image |
Metadata
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