LTX-2.3 based audio model outputs

https://redd.it/1soptsf
@rStableDiffusion

How to Generate an AI Video on Your Own PC Fast and Free (LTX Desktop Tutorial + Troubleshooting)
https://www.youtube.com/watch?v=Gr4q7rw9Xys

https://redd.it/1sorbvq
@rStableDiffusion

ComfyUI Tutorial Extend Your Videos with LTX 2 3 Outpainting
https://youtu.be/L22ARC8GzYI

https://redd.it/1sot3xj
@rStableDiffusion

Ernie shows some strength in infographic (but yes, in photorealism I still prefer ZIT)

https://redd.it/1soramf
@rStableDiffusion

Flux.2 Klein 9B LCS Consistency LoRA 20260415 - Maximum Color Stability Without Sacrificing Editing Capability

Hi everyone,

Following up on my previous Flux.2 Klein 4B Consistency LoRA release, I'm excited to share a major update: the **Flux.2 Klein 9B LCS Consistency LoRA (20260415)**. This version brings significant improvements in color stability and editing flexibility, specifically trained for the Flux.2 Klein 9B model.

In my earlier 4B release, I mentioned that a 9B-compatible version would depend on community interest — and the response was overwhelming. So I went back to training, and this time I focused on solving one of the hardest problems in consistency editing: **maximum color stability without sacrificing editing capability**.

🔍 What's New in the 9B Version:

**Maximum Color Stability:**

* **Latent Color Subspace (LCS) Alignment:** A new training approach that aligns the latent color subspace, ensuring the model maintains color consistency at a fundamental level while preserving far more editing headroom than traditional methods.
* **Latent2Lab Conversion:** Colors are now mapped through a Lab color space conversion during training, resulting in perceptually more accurate and consistent color reproduction across edits.
* **Helios Frame Perturbation:** A novel data augmentation technique that introduces controlled perturbations during training, making the model significantly more robust to input variations and noise.

**Minimal Editing Capability Degradation:**

One of the biggest trade-offs with existing consistency LoRAs is that they tend to lock down the image too aggressively, making it nearly impossible to make meaningful edits. This LoRA is designed differently.

* **Weight at 1.0 — No Tuning Required:** Unlike other consistency LoRAs where you need to carefully dial in weights (0.3–0.7) to balance consistency vs. editability, the LCS Consistency LoRA is designed to work at **full strength (1.0)** right out of the box. No more tedious weight adjustments.
* **High Compatibility:** Works alongside other LoRAs without conflicts. Stack it with your favorite style or detail LoRAs and it plays nicely.

⚠️ IMPORTANT COMPATIBILITY NOTE:

**Model Requirement:** This LoRA is trained EXCLUSIVELY for **Flux.2 Klein 9B Base**. But it could use with turbo lora to achieve 4 steps editing.

**Not Compatible with Flux.2 Klein 4B:** Due to architectural differences between the 4B and 9B models, this LoRA will not work correctly on Flux.2 Klein 4B. If you're using the 4B model, please use the original 4B Consistency LoRA instead.

🛠 Usage Guide:

**Base Model:** Flux.2 Klein 9B Base

**Recommended Strength:** 1.0

**Workflow:** Designed to work seamlessly within ComfyUI. Integrates easily into standard pipelines without requiring complex custom nodes.

🚀 Summary of Improvements Over 4B Version:

|Feature|4B LoRA|9B LCS LoRA|
|:-|:-|:-|
|Color Stability|Good|Maximum (LCS + Latent2Lab)|
|Recommended Weight|0.5 – 0.75|**1.0**|
|Weight Tuning Needed|Yes|No|
|LoRA Compatibility|Moderate|High|
|Editing Flexibility|Moderate|High|

All test images are derived from real-world inputs to demonstrate the model's capacity for consistent reproduction with editing flexibility. I'd love to hear your feedback — especially on how well it handles color consistency across different editing scenarios!

Examples:

https://preview.redd.it/cjr7ao0hruvg1.png?width=3795&format=png&auto=webp&s=215dedb468e86b57645f8220ec342c0db1ab3c8a

https://preview.redd.it/r30ppw4iruvg1.jpg?width=3411&format=pjpg&auto=webp&s=b2576dee2443bd63feb1ff9a0d042b34c5ea33ed

https://preview.redd.it/x3epk68jruvg1.png?width=3075&format=png&auto=webp&s=bf462617476cdb76772f7784371a77115f85c62c

https://preview.redd.it/yk41wfyjruvg1.png?width=4821&format=png&auto=webp&s=63a342bc68c722eb2108bb769d510e2a52a0a99e

https://preview.redd.it/uj36uamkruvg1.png?width=2655&format=png&auto=webp&s=acf3e6c32883843e022e86b6492f170b82af333b

https://preview.redd.it/r7omscwkruvg1.png?width=2655&format=png&auto=webp&s=38ef7be28e05bb5faf4f5170496281ac0f796036

https://preview.redd.it/10e0vnzmruvg1.png?width=2655&format=png&auto=webp&s=1fc666954d3fe85ad7449377c7d108f01f487533



https://redd.it/1sojzpl
@rStableDiffusion

Difference between Klein 4B and Klein 9B is sooo big
https://redd.it/1sow758
@rStableDiffusion

What does LTX actually do with ingested audio?

When you load audio and feed it into LTX's audio latent, it's not like it uses that actual audio in terms of its own generated audio output...

Instead it seems to be 'influenced' by the audio. But that influence seems to vary substantially and be quite weak in general - for example it won't use the accent of the voice fed in

So what does it actually do with the audio? In an ideal world, we'd be able to configure how much it drifts from the audio fed in

https://redd.it/1soxytu
@rStableDiffusion

EditAnything IC-LoRA - LTX-2.3

This model was trained on 8,000 video pairs, and training is still ongoing for a few thousand more steps. It is still experimental, not trained with a fully professional production target, and the model may be updated unexpectedly as new checkpoints.

The current goal is not final polished production quality, but to explore:

edit-anything behavior
prompt-following
inference tradeoffs
synthetic dataset building, especially for style data

The model was trained around four main prompt patterns:

Add
Add a/an [subject/object] with [clear visual attributes], [precise location in the scene].

Remove
Remove the [subject/object] [location or identifying description].

Replace
Replace the [original subject/object] [location] with a/an [new subject/object] with [clear visual attributes].

Convert / Style
Convert the video into a [style name] style.

Workflow URL: `https://huggingface.co/Alissonerdx/LTX-LoRAs/blob/main/workflows/ltx23_edit_anything_v1.json`

Model URL: ltx23\_edit\_anything\_global\_rank128\_v1\_9000steps\_adamw.safetensors · Alissonerdx/LTX-LoRAs at main

Or
CivitAI URL: EditAnything - v1.0 | LTX Video LoRA | Civitai

One important thing during inference is CFG.

A good starting point is testing a distilled setup with CFG = 1. If the edit feels too weak or the model is not following the prompt well enough, increasing CFG can be the key. In some cases, increasing the distill LoRA strength to around 1.2 can also help.

The workflow is also not fully optimized yet. It still needs more testing to find the best combination of:

CFG
LoRA strength
number of steps
model combinations

It may also be interesting to combine this model with other models and see what kinds of results emerge.

If you can test it, please share your findings. Feedback on prompt behavior, edit strength, consistency, style transfer, and failure cases would be very helpful while training is still in progress.

Add a small, brown dog dancing in the foreground next to the woman.

Convert the entire video to an anime style with vibrant colors and exaggerated character expressions.

Remove the blue car in the background of the scene.

Add a wide, genuine smile to the person's face.

Replace the person's clothing with a dark blue hoodie and gray sweatpants.



https://redd.it/1sp03jq
@rStableDiffusion

A new way to reduce the grid on Ernie Image Turbo

https://redd.it/1sow48s
@rStableDiffusion

Not too shabby, for SD1.5 on Pascal IMHO
https://redd.it/1sp0w28
@rStableDiffusion