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what ai tool and prompts they using to get this level of perfection?
https://redd.it/1oijql2
@rStableDiffusion
https://redd.it/1oijql2
@rStableDiffusion
🤯1
Nitro-E: 300M params means 18 img/s, and fast train/finetune
https://huggingface.co/amd/Nitro-E
https://redd.it/1oij9q9
@rStableDiffusion
https://huggingface.co/amd/Nitro-E
https://redd.it/1oij9q9
@rStableDiffusion
Reddit
From the StableDiffusion community on Reddit: Nitro-E: 300M params means 18 img/s, and fast train/finetune
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Looking back on Aura Flow 0.3 - does anyone know what happened?
https://redd.it/1oijk3u
@rStableDiffusion
https://redd.it/1oijk3u
@rStableDiffusion
Reddit
From the StableDiffusion community on Reddit: Looking back on Aura Flow 0.3 - does anyone know what happened?
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Does anybody know why Forge Couple isn't generating the 2 characters?
https://redd.it/1oinxh1
@rStableDiffusion
https://redd.it/1oinxh1
@rStableDiffusion
Reddit
From the StableDiffusion community on Reddit: Does anybody know why Forge Couple isn't generating the 2 characters?
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Just dropped Kani TTS English - a 400M TTS model that's 5x faster than realtime on RTX 4080
https://huggingface.co/nineninesix/kani-tts-400m-en
https://redd.it/1oiv6p8
@rStableDiffusion
https://huggingface.co/nineninesix/kani-tts-400m-en
https://redd.it/1oiv6p8
@rStableDiffusion
Reddit
From the StableDiffusion community on Reddit: Just dropped Kani TTS English - a 400M TTS model that's 5x faster than realtime on…
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Wan prompting tricks, change scene, FLF
So i've been experimenting with this great model img2vid and there are some tricks I found useful I want to share:
1. You can use "immediately cut to the scene...." or "the scene changes and <scene/action denoscription>" or "the scene cuts" or "cut to the next scene" and similar if you want to use your fav img as reference and make drastic changes QUICK and have more useful frames per generation. Inspired by some loras, and it also works most of the time with loras not originally trained for scene changes and even without loras, but scene change startup time may vary. Loras and their set strenghts also has a visible effect on this.
Also I usually start at least two or more runs (with same settings, but different random seeds) - helps with iterating.
2. FLF can be used to make this effect even stronger(!) and more predictable. Works best if you have first frame image and last frame second image composition wise (just rotating the same image makes a huge difference) close to what you want, so wan effectively tries to merge them immediately. So it's closer to having TWO startup references.
These are my experiments with BASE Q5KM model. Basically, it's similar to what Lynx model does (but I fail to make it run, and most KJ workflows, so this improvisation)
121 frames works just fine
Let's discuss and share similar findings
https://redd.it/1oiw57z
@rStableDiffusion
So i've been experimenting with this great model img2vid and there are some tricks I found useful I want to share:
1. You can use "immediately cut to the scene...." or "the scene changes and <scene/action denoscription>" or "the scene cuts" or "cut to the next scene" and similar if you want to use your fav img as reference and make drastic changes QUICK and have more useful frames per generation. Inspired by some loras, and it also works most of the time with loras not originally trained for scene changes and even without loras, but scene change startup time may vary. Loras and their set strenghts also has a visible effect on this.
Also I usually start at least two or more runs (with same settings, but different random seeds) - helps with iterating.
2. FLF can be used to make this effect even stronger(!) and more predictable. Works best if you have first frame image and last frame second image composition wise (just rotating the same image makes a huge difference) close to what you want, so wan effectively tries to merge them immediately. So it's closer to having TWO startup references.
These are my experiments with BASE Q5KM model. Basically, it's similar to what Lynx model does (but I fail to make it run, and most KJ workflows, so this improvisation)
121 frames works just fine
Let's discuss and share similar findings
https://redd.it/1oiw57z
@rStableDiffusion
Reddit
From the StableDiffusion community on Reddit
Explore this post and more from the StableDiffusion community