sd-webui-modelscope-text2video
ainodes-engine | sd-webui-modelscope-text2video | |
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24 | 17 | |
250 | 479 | |
- | - | |
9.3 | 10.0 | |
about 1 month ago | about 1 year ago | |
Python | Python | |
GNU Lesser General Public License v3.0 only | Apache License 2.0 |
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ainodes-engine
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We need 3d interface for stable diffusion
currently working on a pyqt node based app, qt has a lot of 3d power. XmYx/ainodes-engine (github.com)
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aiNodes - daily (comfy) update
1: git clone -b comfy-dev https://github.com/XmYx/ainodes-engine 2: cd ainodes-engine 3: setup_ainodes.bat then you can start ainodes the usual way, but also ComfyUI with run_comfyui.bat. If you install any custom node package for comfy using the comfy manager, those get imported into the desktop engine on next start. Compatibility is WIP, but most image and sampling nodes will work. (Disco Diffusion too) To install the Comfy Manager run the following from ainodes-engine folder: 1: cd src 2: cd ComfyUI 3: cd custom_nodes 4: git clone https://github.com/ltdrdata/ComfyUI-Manager.git
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aiNodes
XmYx/ainodes-engine (github.com) patreon.com/deforum_ainodes
- AUTOMATIC1111 New Extension - Kandinsky
- aiNodes - daily update - Example Graphs with Help
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I created another stable diffusion UI.
And take a look at the node engine if you are interested: https://github.com/XmYx/ainodes-engine
- aiNodes - work continues
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I will pay someone to make me a simple UI for SD
You can see some of our previous open source works at: XmYx/ainodes-engine (github.com)
sd-webui-modelscope-text2video
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New 1.2B parameter text to video model is out, higher quality than modelscope
Working on it https://github.com/deforum-art/sd-webui-modelscope-text2video/pull/96 (also, will rename the repo to just sd-webui-text2video after that)
- This is fine
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Can someone help me understand what happens with VRAM?
They're linked from the main project's REDME.md under the "Where to get the weights" heading. (https://github.com/deforum-art/sd-webui-modelscope-text2video)
- Trump VS Godzilla - ModelScope + Img2Img
- I'm the creator of LoRA. How can I make it better?
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"Melting World" - Text To Video
Workflow: Text to video AUTO1111 extension https://github.com/deforum-art/sd-webui-modelscope-text2video
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Wake up, samurai! ModelScope text2video fine-tuning repo just dropped! Based on Diffusers, requirements start from GTX 3090 at the moment
Please, give it a try and leave your feedback. Soon fine-tuned models are planned to be usable in the Auto1111 plugin https://github.com/deforum-art/sd-webui-modelscope-text2video/issues/48 as well
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ModelScope text2video is reported to be running at 4 GBs of VRAM with enough effort โ still, help needed to bring more optimizations and streamline the process
Meanwhile, if you have good training vids, it'd be nice to collect them somewhere for the future training, like inside the extension repo's Discussions https://github.com/deforum-art/sd-webui-modelscope-text2video/discussions
- The kind of result I'm getting with the new A1111 MS text2video model on a RTX 3060 (12 GB)
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"The Rise Of AI" - Text To Video Short Film
Workflow: Text to video AUTO1111 extension https://github.com/deforum-art/sd-webui-modelscope-text2video
What are some alternatives?
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
diffusers - ๐ค Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
sd-webui-additional-networks
kandinsky2-simplegui - Simple local gui to play with Kandinsky 2
VideoCrafter - VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models
diffuzers - a web ui & api for ๐ค diffusers
Text-To-Video-Finetuning - Finetune ModelScope's Text To Video model using Diffusers ๐งจ
kandinsky-for-automatic1111 - Automatic1111 extension adding support for Kandinsky 2.X
sd-webui-text2video - Auto1111 extension implementing text2video diffusion models (like ModelScope or VideoCrafter) using only Auto1111 webui dependencies
stable-diffusion-webui-extensions - Extension index for stable-diffusion-webui
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.