Bump diffusers from 0.25.0 to 0.27.1

[dependabot]

Bumps diffusers from 0.25.0 to 0.27.1.

Release notes

Sourced from diffusers's releases.

v0.27.1: Clear scale argument confusion for LoRA

All commits

• Release: v0.27.0 by @​DN6 (direct commit on v0.27.1-patch)
• [LoRA] pop the LoRA scale so that it doesn't get propagated to the weeds by @​sayakpaul in #7338
• Release: 0.27.1-patch by @​sayakpaul (direct commit on v0.27.1-patch)

v0.26.3: Patch release to fix DPMSolverSinglestepScheduler and configuring VAE from single file mixin

All commits

• Fix configuring VAE from single file mixin by @​DN6 in #6950
• [DPMSolverSinglestepScheduler] correct get_order_list for solver_order=2and lower_order_final=True by @​yiyixuxu in #6953

v0.26.1: Patch release to fix torchvision dependency

In the v0.26.0 release, we slipped in the torchvision library as a required library, which shouldn't have been the case. This is now fixed.

All commits

• add is_torchvision_available by @​yiyixuxu in #6800

v0.26.0: New video pipelines, single-file checkpoint revamp, multi IP-Adapter inference with multiple images

This new release comes with two new video pipelines, a more unified and consistent experience for single-file checkpoint loading, support for multiple IP-Adapters’ inference with multiple reference images, and more.

I2VGenXL

I2VGenXL is an image-to-video pipeline, proposed in I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models.

import torch
from diffusers import I2VGenXLPipeline
from diffusers.utils import export_to_gif, load_image
repo_id = "ali-vilab/i2vgen-xl"
pipeline = I2VGenXLPipeline.from_pretrained(repo_id, torch_dtype=torch.float16).to("cuda")
pipeline.enable_model_cpu_offload()
image_url = "https://huggingface.co/datasets/diffusers/docs-images/resolve/main/i2vgen_xl_images/img_0001.jpg"
image = load_image(image_url).convert("RGB")
prompt = "A green frog floats on the surface of the water on green lotus leaves, with several pink lotus flowers, in a Chinese painting style."
negative_prompt = "Distorted, discontinuous, Ugly, blurry, low resolution, motionless, static, disfigured, disconnected limbs, Ugly faces, incomplete arms"
generator = torch.manual_seed(8888)
frames = pipeline(
prompt=prompt,
image=image,
num_inference_steps=50,
negative_prompt=negative_prompt,
generator=generator,
).frames
export_to_gif(frames[0], "i2v.gif")

... (truncated)

Commits

• d7634cc Release: 0.27.1-patch
• 1ab57b6 [LoRA] pop the LoRA scale so that it doesn't get propagated to the weeds (#7338)
• cfa7c0a Release: v0.27.0
• 4974b84 Update Cascade Tests (#7324)
• 83062fb [Advanced DreamBooth LoRA SDXL] Support EDM-style training (follow up of #71...
• b6d7e31 add edm schedulers in doc (#7319)
• 53e9aac log loss per image (#7278)
• 4142446 [Tests] Fix incorrect constant in VAE scaling test. (#7301)
• 95de198 add: pytest log installation (#7313)
• 0b45b58 update get_order_list if statement (#7309)
• Additional commits viewable in compare view

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Superseded by #65.