Text from the page:
TheBloke/una-cybertron-7B-v2-AWQ ✦ A 7B MistralAI based model, best on it's series. Trained on SFT, DPO and UNA (Unified Neural Alignment
Text from the page:
you used when fine-tuning.
Metadata about the training job is now diplayed
above
the inputs and outputs to make it easier to see the
Text from the page:
by GenAI. We have a state of arts detection algo available in our webiste
scam.ai
, feel free to have a try!
Replicate
Home
About
Join
Text from the page:
load it and infer with a small num_inference_steps. Note that it is recommendated to set guidance_scale between [0, 1].
Start a local
Text from the page:
model, you’ll need to make it public. If you created your new model using using the web-based training form, it will be private by default
Text from the page:
download these checkpoints.
Inference
After downloading the above peronalized T2I checkpoints, run the following commands to generate
Text from the page:
with the database. Running out of options, we decided to disable the the asynchronous prediction update features, and at 07:31 UTC we
Text from the page:
a model for both text-to-video as well as image+text-to-video usecases
Model Details
Developed by:
Lightricks
Model type:
Diffusion
Text from the page:
Kandinsky 2.1
Model architecture:
Kandinsky 2.1 inherits best practicies from Dall-E 2 and Latent diffucion, while introducing some
Text from the page:
version, so you’ll need to install TestFlight to try it out. Check out out the instructions for installing the beta version here . Next
Text from the page:
game music . Explore Sakemin’s excellent musicgen-chord model that can can generate music based on audio-based chord conditions or text
Text from the page:
to
comfyanonymous
for creating ComfyUI and
fofr
for creating a
Cog compatiable version of it
Prerequisites
To follow this guide, you’ll
Text from the page:
and input parameters affect the output. For our experiment, we used the the WAN2.1 14b text-to-video model with 720p resolution. To do
Text from the page:
a few reasons. First, it just makes sense. Text generation is, by defenition, probabalistic and it will remain difficult, at best, to
Text from the page:
First, it just makes sense. Text generation is, by defenition, probabalistic and it will remain difficult, at best, to train a model
Text from the page:
new model each time: you can keep using your existing model as the desination, and each new completed training will push to it as a new
Text from the page:
We have a better state of arts detection algo available in our webiste
scam.ai
, feel free to have a try!
This model specializes in
Text from the page:
a
flag, so you can keep on generating image after image until your harddrive is full. Generations after the first one will run a bit
Text from the page:
to the token limits when using this model in your workflow, and shortern prompts if artifacts becomes too obvious.
The medium model
Text from the page:
py with sd-v1-4.ckpt Then I paste a downscaled version of the image into it’s center and inpaint around the center using inpaint.py using
Text from the page:
the inpainting step twice.
Then zoom in by upscaling the image and cuting it to the original size while pasting the “center” image in
Text from the page:
you used when fine-tuning.
Metadata about the training job is now diplayed
above
the inputs and outputs to make it easier to see the
Text from the page:
by GenAI. We have a state of arts detection algo available in our webiste
scam.ai
, feel free to have a try!
Replicate
Home
About
Join
Text from the page:
Licence
YOLO-World is under the GPL-v3 Licence and is supported for comercial usage.
Replicate
Home
About
Join us
Terms
Privacy
Status
Text from the page:
a model for both text-to-video as well as image+text-to-video usecases
Model Details
Developed by:
Lightricks
Model type:
Diffusion
Text from the page:
Kandinsky 2.1
Model architecture:
Kandinsky 2.1 inherits best practicies from Dall-E 2 and Latent diffucion, while introducing some
Text from the page:
and push it to Replicate.
Using the terminal (either from your SSH sesion or inside JupyterLab), run the following command to install
Text from the page:
a prediction on an existing model on Replicate.
Run the following commmand in the terminal to download the
Stable Diffusion
model and
Text from the page:
We have a better state of arts detection algo available in our webiste
scam.ai
, feel free to have a try!
This model specializes in
Text from the page:
canvas that will be outpainted, but the checkboard is not actually neccessary. You can choose any color you like for the surrounding
Text from the page:
guide our images using edge detectors, depth maps, segmentation, sketchs, and more.
The best way to see how each of these work is by
Text from the page:
may not be enough for your model. If you need even more space, you can can set up a larger hosted runner on GitHub , then update your
Text from the page:
py with sd-v1-4.ckpt Then I paste a downscaled version of the image into it’s center and inpaint around the center using inpaint.py using
Text from the page:
the inpainting step twice.
Then zoom in by upscaling the image and cuting it to the original size while pasting the “center” image in