Stable Cascade released Within 24 Hours! A New Better And Faster Diffusion Model!
Summary
TLDRThe video discusses the latest AI diffusion model, Stable Cascade, released by Stability AI. The model is built on the Versatile architecture, which allows for faster training with smaller pixel images and produces high-quality images. It supports Latent Control Net IP and LCM, and has been compared favorably to other models in terms of prompt alignment and aesthetic quality. The video demonstrates the model's ability to handle complex text prompts and generate detailed images, showcasing its potential for future AI animations. However, it is currently for research purposes only and not yet available for commercial use.
Takeaways
- 🚀 Stable Cascade is a new AI diffusion model released by Stability AI, showcasing rapid advancements in AI development.
- 🌟 The model is built upon the Verchin architecture, which allows for faster training with smaller pixel images, leading to more efficient image generation.
- 📈 Stable Cascade uses a 24x24 pixel encoding, which is 42 times smaller in training data compared to traditional stable diffusions, enhancing processing speed.
- 🔍 The model supports Latent Control Net (LCN) and LCM, offering more control over image generation and potentially enabling advanced features like face swapping.
- 🔗 A demo page is available for testing the Stable Cascade model, allowing users to experiment with the new diffusion model's capabilities.
- 📝 The model separates the image generation process into three stages: latent generator, latent decoder, and refinement, improving the quality and detail of the final image.
- 🎨 Evaluations show that Stable Cascade outperforms other models in prompt alignment and aesthetic quality, offering better image recognition and handling of multiple elements in text prompts.
- 📊 The model introduces advanced options such as prior guidance scale, prior inference steps, and decoder guidance scale, providing users with more control over the image generation process.
- 📸 Users can input text prompts in a more natural language manner, which the model handles effectively, generating images that closely align with the input prompts.
- 🚫 It's important to note that Stable Cascade is not yet available for commercial purposes and is intended for research and testing at this stage.
- 🔄 The model's capabilities suggest potential future applications in AI animations, offering higher quality and more detailed images compared to current models.
Q & A
What is the name of the new AI diffusion model discussed in the transcript?
-The new AI diffusion model discussed is called 'Stable Cascade'.
Which company developed the Stable Cascade AI model?
-The Stable Cascade AI model was developed by Stability AI.
What is the basis for the Stable Cascade model's architecture?
-The Stable Cascade model is built upon the Verchin architecture.
What is the advantage of using a smaller pixel size for the encoder training in the Stable Cascade model?
-Using a smaller pixel size for the encoder training allows for faster processing and a reduction in training data size, which is 42 times smaller compared to traditional stable diffusions.
How does Stable Cascade support image generation with text input?
-Stable Cascade separates the image generation process into three stages: latent generator, latent decoder, and refinement. It uses text input to generate brief ideas of the image in the latent generator stage, decodes it into pixel representations in the latent decoder stage, and refines the objects in the final stage to produce the full image.
What is the significance of the ControlNet and LCM support in Stable Cascade?
-Support for ControlNet and LCM allows for more precise control over facial identity and other elements during the image generation process, including the ability to handle face swap features within the model.
How does Stable Cascade compare to previous models in terms of prompt alignment and aesthetic quality?
-Stable Cascade outperforms older models in prompt alignment and has a better aesthetic quality score than most, except for Playground version 2, which has a slightly higher score.
What is the current status of Stable Cascade's compatibility with web UI systems like Automatic1111 or Comy UI?
-As of the time of the transcript, Stable Cascade has not been officially released for support in Automatic1111 or Comy UI. However, updates may come in the future to support these systems.
What are the advanced options available for users in the Stable Cascade demo page?
-The advanced options include negative prompts, seed numbers for image generation, width and height settings, prior guidance scale, prior inference steps, and decoder guidance scale.
How does Stable Cascade handle multiple elements in a text prompt for image generation?
-Stable Cascade handles multiple elements of a text prompt effectively, generating images that incorporate all the principles of the prompt, unlike some previous models that struggled with multiple element handling.
What is the current intended purpose of the Stable Cascade AI model?
-As of the time of the transcript, Stable Cascade is intended for research purposes and not yet for commercial use.
What is the significance of the demo page for Stable Cascade on Hugging Face?
-The demo page on Hugging Face allows users to test the Stable Cascade model, explore its capabilities, and see the results of image generation based on various text prompts.
Outlines
🚀 Introduction to Stable Cascade: The New AI Diffusion Model
The video script introduces Stable Cascade, a recently released AI diffusion model by Stability AI. It discusses the rapid development in AI, with new models being released frequently. The presenter highlights the model's foundation on the Versatile architecture, which allows for faster training with smaller pixel images, leading to more efficient image generation. The model also supports advanced features like Laura control net IP adapter and LCM, indicating its potential for integration with various UI systems. A new demo page is mentioned for testing the model, and the presenter expresses enthusiasm about exploring the technical background and capabilities of Stable Cascade.
📈 Evaluating Stable Cascade's Performance and Features
This paragraph delves into the technical performance of Stable Cascade, comparing it with other models like Playground version 2 and SDXL Turbo. It emphasizes the model's superior prompt alignment and aesthetic quality. The presenter discusses the model's three-stage image generation process, which includes a latent generator, latent decoder, and a refinement stage. The benefits of using smaller pixels for encoding are highlighted, along with the model's ability to handle multiple elements from text prompts effectively. The paragraph also mentions additional features like control net for face identity, super resolution for image upscaling, and the potential for training the model with various objects. A live demonstration of the model using a natural language prompt is provided, showcasing its ability to generate detailed and aligned images.
🌐 Exploring Stable Cascade's Demo and GitHub Resources
The presenter shares links to the Stable Cascade demo page and its corresponding GitHub page, inviting viewers to explore and test the model. It is mentioned that the model is not yet available for commercial use but is intended for research purposes. The paragraph includes a discussion about the model's advanced options, such as negative prompts, image dimensions, and new parameters like prior guidance scale and inference steps. The presenter conducts another test using the model with different prompts, demonstrating its ability to generate images with complex details and actions. The limitations regarding the model's commercial use and the need for potential updates to UI systems for compatibility are also discussed.
🎬 Potential Applications and Future Prospects of Stable Cascade
The final paragraph speculates on the potential applications of Stable Cascade in creating AI animations with higher quality than current models. The presenter expresses excitement about the new model and encourages viewers to try it out. They also mention their intention to cover the Stable Video Diffusions update in a future video. The video concludes with a note of inspiration and a farewell, promising to see the audience in the next video.
Mindmap
Keywords
💡AI Diffusion Model
💡Stability AI
💡Verchin Architecture
💡Image Generation Process
💡Text Prompt
💡ControlNet
💡Super Resolution
💡Demo Page
💡GitHub Page
💡Prompt Alignment
💡Aesthetic Quality
Highlights
Stable Cascade is a new AI diffusion model released by Stability AI, built on the Versatile architecture.
The model can train faster with smaller 24x24 pixel images compared to traditional 128x128 pixel images.
It uses 42 times less training data compared to Stable Diffusion 1.5, allowing faster processing even on lower-end GPUs.
The model has three stages - latent generator, latent decoder, and image refinement - using text prompts to generate images.
Stable Cascade outperforms Stable Diffusion 1.5 and SDXL in prompt alignment and aesthetic quality.
The model supports facial control, identity swapping, and advanced control net features.
It also has super resolution capabilities for more detailed image generation.
Stability AI has released a demo page for testing the Stable Cascade model.
The model handles multiple elements in text prompts better than previous Stable Diffusion models.
Users can input prompts in a more natural language style, unlike the older comma-separated style.
The demo page allows users to adjust various settings like negative prompts, image size, and inference steps.
The model is not yet available for commercial use, only for research purposes.
The model can generate high-quality images with detailed elements and actions based on complex text prompts.
The model's image recognition capabilities surpass those of Stable Diffusion 1.5 and SDXL.
The model could potentially be used for creating AI animations with higher quality than current models.
Stability AI may release updates in the future to make the model compatible with web UIs like Automatic1111 and Comfy UI.
Transcripts
let's talk about stable Cascade the new
AI diffusion model just
released so AI have been going really
fast in the development and everything
new AI models release every day look at
hugging face they have everything
listing in here that you see the metav
voice IO well I'm going to talk about
this in uh the large language model
Channel soon and then scroll down into
here I see well stability AI have stable
video diffusions 1.1 well I was going to
do this but then when I scroll up a
little
bit they showed stability AI stable
Cascade and I saw this is like not even
a days ago and 16 hours ago and then I
was checking out this one and I say okay
forget about stable video diffusions 1.1
updates and let's do this
one because when I saw this one they
said this model is built up on the ver
Chen architecture and I have mentioned
this diffusion model previously in my
YouTube channel which is here this is
the
sausage and where this name I search it
is actually a German language of a
sausage and well that's how I came up
with the thumbnails of this videos and
then I saw this is very interesting that
stable diffusion newer model from
stability AI they are creating a new
diffusions model using the vers chin and
then we had talked about this
architecture before it is able to train
diffusions model faster speed with
smaller pixels image and you are able to
produce sdxl standard size image like
this one we have 1024x 1024 image but
then their encoding of this architecture
is using 24x 24 PX eels instead of that
it is 42 times smaller training data
compared with traditional stable
diffusions 1.5 128 by 128 pixels and it
is even faster than sdxl because well
why not right you do something newer
model of course it's going to be
performed better than the older AI
models and one thing is really good
about this model stable Cascade created
by stability AI they are also supporting
for Laura control net IP adapter and LCM
like oh my goodness this is insane if
there's new updates for automatic 1111
or comy UI any web UI system that will
support stable diffusions I believe
later on we will have an update that can
support this stable Cascade AI models to
run image Generations on those system
and one of the very good news about that
is that they have a new demo page that
we will be testing out this model and
right now they have not officially
released any support in auto automatic
11 or com vui at this moment they just
updated today within just 24 hours so
I'm going to just say okay forget about
stable video diffusions update and let's
do this one first so this model let's go
through their overview and some
technical backgrounds about this one
first of all you see this model stable
Cascade they are separating with three
stages of image generation process which
we call it the latent generator and the
latent generator in stage C they
generate this using the text your input
text that means your text prompt
generating the brief ideas of the image
and then they pass it to the Stage B to
do the latent decoder so that it allows
the AI to put those pixels those little
little do pixels put it back into this
whole objects and then through these
objects they can be refined tuned in
stage a and you will be getting a full
image of your result so within this one
they are using better I would say better
performance than stable diffusions since
they are using a smaller size pixels for
their encoder training and then the
processing data is smaller size that is
like 42 times compared with the
traditional stable diffusion so that is
really Advantage for us to processing
faster even you have lower-end GPU
graphic card or high-end graphic cards
both of them are able to have advantage
to generate image faster and one of the
really good thing that I saw in here
they have the evaluations you got the
prom alignment and the aesthetic quality
they have compared with playground
version 2 and sdxl turbo and sdxl and
then the version version 2 so in the
prompt alignment of them are suppressing
those older model that currently on the
market and then in the aesthetic quality
the playground 2 version 2 is a little
bit higher score than the stable Cascade
but it is way better than other three
diffusions model in here as they test in
the this is like the benchmarking result
from their testing phase so let's go to
their demo page in hugging
phase right now we have this page now I
will share the links of this hugging
face demo page and also the model card
in here as well and and also they have
GitHub page that is talking about the
same thing of what we saw in the hugging
face model card the same information is
in here and you can check this out as
well and also they have more details
about the text prompt that you are going
to input that is not like those stable
diffusions 1.5 stylus text prompt and
this is more like a natural language
manner of input prompts for creating a
new image in this new model and also
they have control net here as you can
see you can control the face the face
identity and then well if you have the
face identity that means they have
already handled the face swap features
within the model I will believe that is
so and then they have the candy's
control net that is going to just like
other stable diffusion control net that
we used to do and then the super
resolutions that means they have
something like an upscaling for making
your image more details and more
refinement on all the detail small part
of your AI image and then you can easily
train your lorus with any objects for
example they have a dog of this and then
they train with this image and they can
reproduce this image with a space suit
of the dog wearing a space suit and then
the image recognitions are well I can
say it's better than stable diffusion
1.5 or sdxl because their training is
they have more image training for their
their models without this principle it
has already suppressed the image
recognition of the older stable
diffusions model okay so let's go to the
demo page right here let's try this out
now I have tried one time with a very
simple prompt in here I say the
playground an old man walking with his
grandson holding hand and sunset time
now this is not like the old days the
traditional text prompts in stable
diffusions 1.5 as you can see we are
using a more natural language sentence
almost like a sentence to create an
image like this now as I can see the
image in here is well it's pretty nice
let's go to a new tab and we can check
out the full size of it now as you can
see all these prompts in here it does
generating into the image already
there's a grandson and then the old man
is holding hands together in a
playground and then the sunset time
basically all the principle of my
prompts is already appear on this image
and it does really well to handle
multiple elements of a text prompt
rather than in stable diffusions 1.5 or
even
sdxl sometimes you cannot do multiple
element handling which means they are
not in here they have set the prompt
alignment which means they have not did
that quite good in sdxl and even the
older one the SD 1.5 but then in here
it's done really well right and then you
can see in here they have the advanced
options that you can of course you put
negative prompts you can generate seat
numbers that is very typical for all AI
models especially for image generation
models and then you can set your width
and height in here and that is the same
size of sdxl by default of this AI model
and then numbers of image and then this
one is kind of a new thing for us as a
stable diffusions user the prior guide
idance scale and then the prior
inference steps and then the decoder
guidance scale this is something and
also the lastly in here the inference
steps this is something that we don't
have in stable diffusions well the steps
we can classify this one can be the
sampling steps like how much you want to
set in 25 step or 30 step Etc but then
the other two from this decoder scales
and then the decoder steps in here it is
something that we don't have in stable
diff fusions currently so I guess if
they have to implement this model into
comfy UI or automatic 1111 they have to
create a new notes in there or a new
input data area for us to set these two
parameters in automatic 1111 as well so
I'm waiting if they have an update about
this model can be compatible with both
automatic or comy UI but at this moment
right now we are able to test the stable
Cascade in this demo page of hugging
face and the GitHub page in here allows
you to download the coding on the top of
here you can download this code and this
is also the same demo page in here but
you can run it in locally but I guess it
is not the point for us to download this
demo page locally using the GitHub page
project instead just enjoy and try in
this GitHub demo page at this moment and
let's wait for the updates if they are
supporting in other web UI like
automatic 1111 or comy UI then we can
fully enjoy this model using in those
system right so let's try another
example in here that using their default
text I will say this is a pretty cool
thing like a city of Los Angeles this
one and let's try
this okay so here we have the result
here that is kind of funny thing you're
putting something that is not realistic
but it is in realistic styles of Los
Angeles Street and you see all these
details of the street and then of the
concrete on the top here see all those
Mark they have did very detail on this
and it looks pretty good and let's try
some prompts that not by default in here
uh let's say uh you know in previous
videos I have tests about the versen
diffusions model I have test John Wick
and let's try with this one John Wick in
cyberpunk and let's try in diffusion
Cascade so let's say John Wick John Wick
closeup shot
okay actually let's not going to do the
traditional text Palm let's do something
like John Wick in Disco clapping places
he hold pistol ready to shoot the place
with cyberpunk Leon
light okay let's try this one like more
natural language prompts that is not
like those one keyword and comma one
keyword and then another comma those
table diffusions 1.5 text prompt Styles
hopefully it will generate something for
me
and there you go more clear and
hopefully there is something and let's
see the full view of
this well the eyes is not kind of clear
at this moment but we can see okay
there's like the Assassin's ring and
he's showing very detail of that and
then the wash but then John Wick is
carrying the wash in other side and
actually inside the hand wrist of the
watch should be facing inside I should
say but it does doing something
realistic kind of like everything in
here is following my prom really well
like in a disco clubbing Pace holding a
pistol ready to shoot so the action of
John Wick is ready to shooting the
pistol and then you see the Cyber Punk
Leon light is all over here so I can say
this is a pass but then the eyes of this
we might need a refinder to do that if
we need to enhance this image let's say
if let's let's try with this problem
again with more content and I would say
let's fix the eyes okay with John Wick
picture with clear face and eyes just do
that okay just add one more content in
here let's hope that it can help for our
character face with better
quality
now one thing I have to mention about
this AI model is that it is not for
commercial purpose yet okay maybe one
day you can purchase this AI models for
the license for commercial purpose but
right now we are just doing it for
research purpose okay so another one
here yeah we have a better phas more
clear and similar Styles I would say
well the pistol is kind of awkward in
this direction Direction well if you
guys have played with Firearms before
and you would know that the wrists of
this and then the angles of the pistol
pointing is kind of awkward way it
should be more pointing in the center of
the character instead of pointing
outward of the character but oh well I
would still give it a pass for this
right this style compared with the
previous one the purely trained one chai
diffusions model the older diffusion
model of this sausage model's name is
always giving me the close upshot of a
character but then in the stable Cascade
they have given me more element and
actions of the characters there is more
content in the generate image within
this sort of prompts so I would say yes
their quality have suppressed the one
child version to already a lot I mean it
should say a lot and then of course they
are suppressing the sdxl a lot as well
and I can see that if we are able to use
this model in the future and we can make
AI animations using this model instead
of SD 1.5 or
sdxl and of course we can do way better
quality than what we have in today in AI
elements so it I hope you guys enjoyed
these videos have a quick test I just
did a very fast videos quick fast videos
about this newer models I really want to
do it today to share it with you guys
and um yeah maybe the stable video
diffusions uh newer update 1.1 I would
do it next time in other videos but then
I hope you guys can get inspired of this
new models stable Cascade and then try
it out this is a very exciting news for
me and I hope you guys do so I will see
you guys in the next videos and have a
nice day
bye
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