diffusers-AutoPipline

本文主要是介绍diffusers-AutoPipline，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

https://huggingface.co/docs/diffusers/tutorials/autopipelinehttps://huggingface.co/docs/diffusers/tutorials/autopipelineAutoPipeline会自动检测要使用的正确流程类，这样可以更轻松地加载与任务相对应的检查点，而无需知道具体的流程类名称。

1.choose an autopipeline for your task

from diffusers import AutoPipelineForText2Image
import torchpipeline = AutoPipelineForText2Image.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16, use_safetensors=True
).to("cuda")
prompt = "peasant and dragon combat, wood cutting style, viking era, bevel with rune"image = pipeline(prompt, num_inference_steps=25).images[0]

AutoPipelineForText2Image：

1.自动从model_index.json文件中检测到一个名为"stable-diffusion"的类。2.基于"stable-diffusion"类名加载相应的文本到图像的StableDiffusionPipeline。

from diffusers import AutoPipelineForImage2Imagepipeline = AutoPipelineForImage2Image.from_pretrained("runwayml/stable-diffusion-v1-5",torch_dtype=torch.float16,use_safetensors=True,
).to("cuda")
prompt = "a portrait of a dog wearing a pearl earring"url = "https://upload.wikimedia.org/wikipedia/commons/thumb/0/0f/1665_Girl_with_a_Pearl_Earring.jpg/800px-1665_Girl_with_a_Pearl_Earring.jpg"response = requests.get(url)
image = Image.open(BytesIO(response.content)).convert("RGB")
image.thumbnail((768, 768))image = pipeline(prompt, image, num_inference_steps=200, strength=0.75, guidance_scale=10.5).images[0]

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