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92 lines
3.6 KiB
Markdown
92 lines
3.6 KiB
Markdown
# 模型推理
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本文档以 Qwen-Image 模型为例，介绍如何使用 `DiffSynth-Studio` 进行模型推理。
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## 加载模型
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模型通过 `from_pretrained` 加载：
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```python
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from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
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import torch
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pipe = QwenImagePipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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model_configs=[
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ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
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ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="text_encoder/model*.safetensors"),
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ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
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],
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tokenizer_config=ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="tokenizer/"),
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)
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```
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其中 `torch_dtype` 和 `device` 是计算精度和计算设备（不是模型的精度和设备）。`model_configs` 可通过多种方式配置模型路径，关于本项目内部是如何加载模型的，请参考 [`diffsynth.core.loader`](/docs/API_Reference/core/loader.md)。
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<details>
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<summary>从远程下载模型并加载</summary>
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> `DiffSynth-Studio` 默认从[魔搭社区](https://www.modelscope.cn/)下载并加载模型，需填写 `model_id` 和 `origin_file_pattern`，例如
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>
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> ```python
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> ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
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> ```
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>
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> 模型文件默认下载到 `./models` 路径，该路径可通过[环境变量 DIFFSYNTH_MODEL_BASE_PATH](/docs/Pipeline_Usage/Environment_Variables.md#diffsynth_model_base_path) 修改。
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>
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> 默认情况下，即使模型已经下载完毕，程序仍会向远程查询是否有遗漏文件，如果要完全关闭远程请求，请将[环境变量 DIFFSYNTH_SKIP_DOWNLOAD](/docs/Pipeline_Usage/Environment_Variables.md#diffsynth_skip_download) 设置为 `True`。
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</details>
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<details>
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<summary>从本地文件路径加载模型</summary>
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> 填写 `path`，例如
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>
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> ```python
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> ModelConfig(path="models/xxx.safetensors")
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> ```
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>
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> 对于从多个文件加载的模型，使用列表即可，例如
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>
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> ```python
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> ModelConfig(path=[
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> "models/Qwen/Qwen-Image/text_encoder/model-00001-of-00004.safetensors",
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> "models/Qwen/Qwen-Image/text_encoder/model-00002-of-00004.safetensors",
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> "models/Qwen/Qwen-Image/text_encoder/model-00003-of-00004.safetensors",
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> "models/Qwen/Qwen-Image/text_encoder/model-00004-of-00004.safetensors",
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> ])
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> ```
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</details>
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## 启动推理
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输入提示词，即可启动推理过程，生成一张图片。
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```python
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from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
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import torch
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pipe = QwenImagePipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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model_configs=[
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ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
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ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="text_encoder/model*.safetensors"),
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ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
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],
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tokenizer_config=ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="tokenizer/"),
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)
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prompt = "精致肖像，水下少女，蓝裙飘逸，发丝轻扬，光影透澈，气泡环绕，面容恬静，细节精致，梦幻唯美。"
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image = pipe(prompt, seed=0, num_inference_steps=40)
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image.save("image.jpg")
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```
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每个模型 `Pipeline` 的输入参数不同，请参考各模型的文档。
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如果模型参数量太大，导致显存不足，请开启[显存管理](./VRAM_management.md)。
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