diffusers提供text to image,image to image和inpainting三种类别的pipeline,每种pipeline都提供标准pipeline和controlnet pipeline两类。 构建一个pipeline很简单: from diffusers import StableDiffusionPipeline import torch pipe = StableDiffusionPipeline.from_pretrained( pretrained_model_name_or_path="", torch_...
import torchfrom diffusers import StableDiffusion3Pipelinefrom transformers import T5EncoderModel, BitsAndBytesConfig# Make sure you have `bitsandbytes` installed.quantization_config = BitsAndBytesConfig(load_in_8bit=True)model_id = "stabilityai/stable-diffusion-3-medium-diffusers"text_encoder = T5Enc...
整个Diffusers大概是分为3个核心的大模块,一块是 Pipeline,一块是Model,最后一个是调度器-Schelduler 推理测 核心推理接口-Pipeline类 在课程的对应示例,常用的调用Stable Diffusion Pipeline的接口是下面的这个 from diffusers import StableDiffusionPipeline #model_id = "runwayml/stable-diffusion-v1-5" model_id...
python ./scripts/convert_original_stable_diffusion_to_diffusers.py --checkpoint_path xxx.ckpt --dump_path save_dir 转换完成后，可直接利用 diffusers 的 API 进行模型加载 from diffusers import StableDiffusionPipeline pipeline = StableDiffusionPipeline.from_pretrained (save_dir,torch_dtype=torch.float3...
Stable Diffusion 3.5 的 transformer 模型还可以使用 Stability AI 发布的原生参数文件来进行初始化 。这里需要使用 from_single_file 方法:import torchfrom diffusers import SD3Transformer2DModel, StableDiffusion3Pipelinetransformer = SD3Transformer2DModel.from_single_file("https://huggingface.co/stabilityai/...
Stable Diffusion 3.5 的 transformer 模型还可以使用 Stability AI 发布的原生参数文件来进行初始化 。这里需要使用from_single_file方法: importtorchfromdiffusersimportSD3Transformer2DModel,StableDiffusion3Pipeline transformer=SD3Transformer2DModel.from_single_file("https://huggingface.co/stabilityai/stable-diffusion...
pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", text_encoder_3=None, tokenizer_3=None, torch_dtype=torch.float16) pipe = pipe.to("cuda") prompt ="smiling cartoon dog sits at a table, coffee mug on hand, as a room goes up in flames. ...
作为Stable Diffusion 3的改进版本,Stable Diffusion 3.5 如今已在 Hugging Face Hub 中可用,并可以直接使用 🧨 Diffusers 中的代码运行。 本次发布包含两套模型参数: 一个大型的模型 (large,8B) 该模型经过时间步蒸馏的版本,仅需几步推理即可生成图片 ...
pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", text_encoder_3=None, tokenizer_3=None, torch_dtype=torch.float16) pipe = pipe.to("cuda") prompt ="smiling cartoon dog sits at a table, coffee mug on hand, as a room goes up in flames. ...
pipe=StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers",torch_dtype=torch.float16)pipe=pipe.to("cuda")image=pipe("A cat holding a sign that says hello world",negative_prompt="",num_inference_steps=28,guidance_scale=7.0,).images[0]image ...