From 2ea22e1cc7188ee14d41112be1b3413aa1e920c5 Mon Sep 17 00:00:00 2001 From: Aryan Date: Fri, 2 Aug 2024 02:47:40 +0530 Subject: [PATCH] [docs] fix pia example (#9015) fix pia example docstring --- src/diffusers/pipelines/pia/pipeline_pia.py | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/src/diffusers/pipelines/pia/pipeline_pia.py b/src/diffusers/pipelines/pia/pipeline_pia.py index f383af7cc1..f0e8cfb03d 100644 --- a/src/diffusers/pipelines/pia/pipeline_pia.py +++ b/src/diffusers/pipelines/pia/pipeline_pia.py @@ -54,22 +54,21 @@ EXAMPLE_DOC_STRING = """ Examples: ```py >>> import torch - >>> from diffusers import ( - ... EulerDiscreteScheduler, - ... MotionAdapter, - ... PIAPipeline, - ... ) + >>> from diffusers import EulerDiscreteScheduler, MotionAdapter, PIAPipeline >>> from diffusers.utils import export_to_gif, load_image - >>> adapter = MotionAdapter.from_pretrained("../checkpoints/pia-diffusers") - >>> pipe = PIAPipeline.from_pretrained("SG161222/Realistic_Vision_V6.0_B1_noVAE", motion_adapter=adapter) + >>> adapter = MotionAdapter.from_pretrained("openmmlab/PIA-condition-adapter") + >>> pipe = PIAPipeline.from_pretrained( + ... "SG161222/Realistic_Vision_V6.0_B1_noVAE", motion_adapter=adapter, torch_dtype=torch.float16 + ... ) + >>> pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config) >>> image = load_image( ... "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/pix2pix/cat_6.png?download=true" ... ) >>> image = image.resize((512, 512)) >>> prompt = "cat in a hat" - >>> negative_prompt = "wrong white balance, dark, sketches,worst quality,low quality, deformed, distorted, disfigured, bad eyes, wrong lips,weird mouth, bad teeth, mutated hands and fingers, bad anatomy,wrong anatomy, amputation, extra limb, missing limb, floating,limbs, disconnected limbs, mutation, ugly, disgusting, bad_pictures, negative_hand-neg" + >>> negative_prompt = "wrong white balance, dark, sketches, worst quality, low quality, deformed, distorted" >>> generator = torch.Generator("cpu").manual_seed(0) >>> output = pipe(image=image, prompt=prompt, negative_prompt=negative_prompt, generator=generator) >>> frames = output.frames[0]