save intermediate

models/vision/glide/run_glide.py

-import torch
-
-import PIL.Image
-from diffusers import DiffusionPipeline
-
-
-generator = torch.Generator()
-generator = generator.manual_seed(0)
-
-model_id = "fusing/glide-base"
-
-# load model and scheduler
-pipeline = DiffusionPipeline.from_pretrained(model_id)
-
-# run inference (text-conditioned denoising + upscaling)
-img = pipeline("a crayon drawing of a corgi", generator)
-
-# process image to PIL
-img = img.squeeze(0)
-img = ((img + 1) * 127.5).round().clamp(0, 255).to(torch.uint8).cpu().numpy()
-image_pil = PIL.Image.fromarray(img)
-
-# save image
-image_pil.save("test.png")