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Dhruv Nair PRO

dn6

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posted an update 7 months ago

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2881

Sharing for anyone using Diffusers from_single_file loading and affected by the Runway SD 1.5 issue.

If you have runwayml/stable-diffusion-v1-5 saved locally in your HF cache then loading single file checkpoints in the following way should still work.

from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_single_file("<url or path to single file checkpoint>")

If you do not have the model repo saved in your cache, then automatically inferring the pipeline config will not work since the reference repo runwayml/stable-diffusion-v1-5 doesn't exist anymore.

You can use an alternative SD1.5 repo id to still configure your pipeline.

from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_single_file("<url or path to single file checkpoint>", config="Lykon/DreamShaper")

We're working on resolving the issue ASAP.

2 replies

reacted to sayakpaul's post with 🚀 10 months ago

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1898

🧨 Diffusers 0.28.0 is out 🔥

It features the first non-generative pipeline of the library -- Marigold 🥁

Marigold shines at performing Depth Estimation and Surface Normal Estimation. It was contributed by @toshas , one of the authors of Marigold.

This release also features a massive refactor (led by @DN6 ) of the from_single_file() method, highlighting our efforts for making our library more amenable to community features 🤗

Check out the release notes here:
https://github.com/huggingface/diffusers/releases/tag/v0.28.0

reacted to akhaliq's post with 🚀 about 1 year ago

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Mora

Enabling Generalist Video Generation via A Multi-Agent Framework

Mora: Enabling Generalist Video Generation via A Multi-Agent Framework (2403.13248)

Sora is the first large-scale generalist video generation model that garnered significant attention across society. Since its launch by OpenAI in February 2024, no other video generation models have paralleled {Sora}'s performance or its capacity to support a broad spectrum of video generation tasks. Additionally, there are only a few fully published video generation models, with the majority being closed-source. To address this gap, this paper proposes a new multi-agent framework Mora, which incorporates several advanced visual AI agents to replicate generalist video generation demonstrated by Sora. In particular, Mora can utilize multiple visual agents and successfully mimic Sora's video generation capabilities in various tasks, such as (1) text-to-video generation, (2) text-conditional image-to-video generation, (3) extend generated videos, (4) video-to-video editing, (5) connect videos and (6) simulate digital worlds. Our extensive experimental results show that Mora achieves performance that is proximate to that of Sora in various tasks. However, there exists an obvious performance gap between our work and Sora when assessed holistically. In summary, we hope this project can guide the future trajectory of video generation through collaborative AI agents.