1条回答 默认 最新
关注- 你可以参考下这篇文章:AI绘图风格对照表/画风样稿详细研究记录及经验总结(分析Midjourney和Stable Diffusion风格提示词实际使用情况)不断更新中...
- 除此之外, 这篇博客: 爱做梦的人工智能「Stabled Diffusion」中的 2.4.2 模型载入 部分也许能够解决你的问题, 你可以仔细阅读以下内容或跳转源博客中阅读:
if fp_mode == "fp32": print("使用全精度推理大小为 512*512 以上的图像时需要占用超过12GB的运行内存") model_id = "./models/snapshots/fdd29747e61912eb941322ef6f592ae6d0e0de19" if not os.path.isdir(model_id): model_id = "CompVis/stable-diffusion-v1-4" if sd_mode == "DDIM": scheduler = DDIMScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", clip_sample=False, set_alpha_to_one=False) elif sd_mode == "PNDM": scheduler = PNDMScheduler.from_config(model_id, subfolder="scheduler", use_auth_token=True) else: print("Current sd_mode only support DDIM or PNDM") sys.exit() pipe = StableDiffusionImgToImgPipeline.from_pretrained(model_id, scheduler=scheduler, use_auth_token=True).to(device) elif fp_mode == "fp16": print("使用半精度推理大小为 512*512 以上的图像时需要占用超过10GB的运行内存") model_id = "./models/snapshots/a304b1ab1b59dd6c3ba9c40705c29c6de4144096" if not os.path.isdir(model_id): model_id = "CompVis/stable-diffusion-v1-4" if sd_mode == "DDIM": scheduler = DDIMScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", clip_sample=False, set_alpha_to_one=False) elif sd_mode == "PNDM": scheduler = PNDMScheduler.from_config(model_id, subfolder="scheduler", use_auth_token=True) else: print("Current sd_mode only support DDIM or PNDM") sys.exit() pipe = StableDiffusionImgToImgPipeline.from_pretrained(model_id, scheduler=scheduler, revision="fp16", torch_dtype=torch.float16, use_auth_token=True).to(device)
解决 无用评论 打赏 举报

