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36 lines
1.8 KiB
Markdown
36 lines
1.8 KiB
Markdown
# Prompt Processing
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DiffSynth includes prompt processing functionality, which is divided into:
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- **Prompt Refiners (`prompt_refiner_classes`)**: Includes prompt refinement, prompt translation from Chinese to English, and both refinement and translation of prompts. Available parameters are as follows:
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- **English Prompt Refinement**: 'BeautifulPrompt', using the model [pai-bloom-1b1-text2prompt-sd](https://modelscope.cn/models/AI-ModelScope/pai-bloom-1b1-text2prompt-sd).
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- **Prompt Translation from Chinese to English**: 'Translator', using the model [opus-mt-zh-e](https://modelscope.cn/models/moxying/opus-mt-zh-en).
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- **Prompt Translation and Refinement**: 'QwenPrompt', using the model [Qwen2-1.5B-Instruct](https://modelscope.cn/models/qwen/Qwen2-1.5B-Instruct).
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- **Prompt Extenders (`prompt_extender_classes`)**: Based on Omost's prompt partition control expansion. Available parameter is:
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- **Prompt Partition Expansion**: 'OmostPromter'.
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## Usage Instructions
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### Prompt Refiners
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When loading the model pipeline, you can specify the desired prompt refiner functionality using the `prompt_refiner_classes` parameter. For example code, refer to [sd_prompt_refining.py](examples/image_synthesis/sd_prompt_refining.py).
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Available `prompt_refiner_classes` parameters include: Translator, BeautifulPrompt, QwenPrompt.
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```python
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pipe = SDXLImagePipeline.from_model_manager(model_manager, prompt_refiner_classes=[Translator, BeautifulPrompt])
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```
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### Prompt Extenders
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When loading the model pipeline, you can specify the desired prompt extender using the `prompt_extender_classes` parameter. For example code, refer to [omost_flux_text_to_image.py](examples/image_synthesis/omost_flux_text_to_image.py).
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```python
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pipe = FluxImagePipeline.from_model_manager(model_manager, prompt_extender_classes=[OmostPromter])
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```
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