Total runs:
26.3K
Run Growth:
-9.4K
Growth Rate:
-35.61%
Sponsored by
AdsCreator.com
joyfox / LTX2.3-ICEdit-Insight
Model's Last Updated: July 23 2026
video-to-video
Introduction of LTX2.3-ICEdit-Insight
Model Details of LTX2.3-ICEdit-Insight
LTX2.3-ICEdit-Insight
|
Research-oriented model release for task-aware video restoration and editing under the
LTX-2.3
framework.
Project links: GitHub project | Valiant Cat on Hugging Face
This repository contains:
-
ltx-2.3-edit-insight-dev-fp8.safetensors- the all-in-one Insight checkpoint
- includes transformer + video VAE + audio VAE + text projection + vocoder
-
ltx2.3-video-upscale-v2.safetensors- IC-LoRA for video super-resolution and detail recovery
-
ltx2.3-ic-watermarkeRM.safetensors- IC-LoRA for video watermark removal and occlusion restoration
These weights are intended to be used with the project's
run_pipeline.py
workflow. The recommended default is single-stage inference, where the IC-LoRA guidance remains active through the full-resolution denoising pass.
Research Positioning
ltx-2.3-edit-insight-dev-fp8.safetensors
is not presented as a bare deployment checkpoint. It is the unified base model release for the Insight branch of this project: a task-aware spatiotemporal editing backbone that consolidates the diffusion transformer, video VAE, audio VAE, text projection module, and vocoder into a single reproducible artifact.
From a research perspective, the checkpoint is intended to support controlled video restoration and editing under a shared latent diffusion formulation. The paired IC-LoRA adapters specialize the backbone toward structure-preserving super-resolution and watermark-aware content recovery, while the unified checkpoint packaging keeps the full generative stack aligned for repeatable experiments and downstream ablations.
English Overview
This package is built for the Insight version of the project's LTX-2.3 editing pipeline. Instead of shipping only task adapters, it also includes the corresponding Insight base checkpoint so the workflow can be reproduced with the exact model assets used by the project.
Recommended usage:
-
run the companion
run_pipeline.py - keep single-stage inference enabled by default
- load one task LoRA at a time depending on the editing goal
🧠 Training
This model was trained and optimized by the AI Laboratory of Chongqing Valiant Cat Technology Co., LTD.
Visit vvicat.com for business collaborations or research partnerships.
🧩 Integration with ComfyUI
This model works with the modified ComfyUI workflows provided by the project.
For ComfyUI-based editing, load the base model in the UNet-side model path required by the workflow, then attach the task-specific IC-LoRA for the corresponding edit objective.
Files
| File | Purpose |
|---|---|
ltx-2.3-edit-insight-dev-fp8.safetensors
|
All-in-one Insight base checkpoint |
ltx2.3-video-upscale-v2.safetensors
|
Super-resolution / detail enhancement IC-LoRA |
ltx2.3-ic-watermarkeRM.safetensors
|
Watermark removal / occlusion restoration IC-LoRA |
Showcase
|
|
Usage With This Project
Run all commands from the project root.
Super-resolution
PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
python run_pipeline.py \
--mode upscale \
--video ./inputs/input.mp4 \
--prompt "Convert the video to ultra-high definition quality, rebuilding high-frequency details while eliminating artifacts." \
--output ./outputs/output_upscale.mp4 \
--height 1184 --width 704 --num-frames 97 \
--fps 24.0 --seed 42 \
--sigma-profile workflow \
--model-checkpoint ./models/checkpoints/ltx-2.3-edit-insight-dev-fp8.safetensors \
--lora ./models/loras/ltx2.3-train/ltx2.3-video-upscale-v2.safetensors
Watermark removal
PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
python run_pipeline.py \
--mode watermark_rm \
--video ./inputs/input.mp4 \
--prompt "Remove short-video platform watermarks and related occlusions from the video, restoring a clean, clear, and natural original image." \
--output ./outputs/output_watermark_rm.mp4 \
--height 1184 --width 704 --num-frames 97 \
--fps 24.0 --seed 1546 \
--sigma-profile workflow \
--model-checkpoint ./models/checkpoints/ltx-2.3-edit-insight-dev-fp8.safetensors \
--lora ./models/loras/ltx2.3-train/ltx2.3-ic-watermarkeRM.safetensors
Notes
- Single-stage inference is the default recommendation.
- In two-stage mode, the second-stage refinement does not keep the IC-LoRA constraint, which can increase content drift.
-
Frame count must satisfy
8k + 1. -
Single-stage output height and width should be multiples of
32.
License
This repository is released under the Apache 2.0 license.
Runs of joyfox LTX2.3-ICEdit-Insight on huggingface.co
18.9K
Total runs
0
24-hour runs
1.9K
3-day runs
854
7-day runs
-16.3K
30-day runs
More Information About LTX2.3-ICEdit-Insight huggingface.co Model
Url of LTX2.3-ICEdit-Insight
LTX2.3-ICEdit-Insight huggingface.co Url
Provider of LTX2.3-ICEdit-Insight huggingface.co
Other API from joyfox
Updated:March 30 2026
Total runs:
20.3K
Run Growth:
523
Growth Rate:
2.62%
Total runs:
12.1K
Run Growth:
-2.3K
Growth Rate:
-19.52%
Total runs:
10.0K
Run Growth:
2.0K
Growth Rate:
19.65%
Total runs:
1.4K
Run Growth:
-379
Growth Rate:
-34.64%
Total runs:
1.0K
Run Growth:
633
Growth Rate:
62.49%
Total runs:
1.0K
Run Growth:
306
Growth Rate:
29.59%
Total runs:
406
Run Growth:
-912
Growth Rate:
-221.90%
Total runs:
316
Run Growth:
22
Growth Rate:
6.88%
Total runs:
287
Run Growth:
36
Growth Rate:
11.69%
Total runs:
238
Run Growth:
-1
Growth Rate:
-0.42%
Total runs:
177
Run Growth:
141
Growth Rate:
79.66%
Total runs:
154
Run Growth:
102
Growth Rate:
66.23%
Total runs:
76
Run Growth:
46
Growth Rate:
60.53%
Total runs:
58
Run Growth:
-6
Growth Rate:
-10.34%
Total runs:
56
Run Growth:
32
Growth Rate:
54.24%
Total runs:
55
Run Growth:
55
Growth Rate:
100.00%
Total runs:
52
Run Growth:
23
Growth Rate:
40.35%
Total runs:
36
Run Growth:
1
Growth Rate:
2.78%
Total runs:
35
Run Growth:
-8
Growth Rate:
-22.86%
Total runs:
34
Run Growth:
17
Growth Rate:
50.00%
Total runs:
31
Run Growth:
5
Growth Rate:
16.67%
Total runs:
29
Run Growth:
-21
Growth Rate:
-72.41%
Total runs:
27
Run Growth:
-14
Growth Rate:
-51.85%
Total runs:
23
Run Growth:
0
Growth Rate:
0.00%
Total runs:
21
Run Growth:
-8
Growth Rate:
-38.10%
Total runs:
21
Run Growth:
4
Growth Rate:
19.05%
Total runs:
20
Run Growth:
8
Growth Rate:
40.00%
Total runs:
16
Run Growth:
1
Growth Rate:
6.25%
Total runs:
15
Run Growth:
-6
Growth Rate:
-40.00%
Total runs:
15
Run Growth:
-12
Growth Rate:
-92.31%
Total runs:
13
Run Growth:
5
Growth Rate:
38.46%
Total runs:
12
Run Growth:
1
Growth Rate:
8.33%
Total runs:
11
Run Growth:
-2
Growth Rate:
-18.18%
Total runs:
11
Run Growth:
2
Growth Rate:
18.18%
Total runs:
10
Run Growth:
-19
Growth Rate:
-190.00%
Total runs:
9
Run Growth:
-4
Growth Rate:
-44.44%
Total runs:
5
Run Growth:
-6
Growth Rate:
-120.00%
Total runs:
4
Run Growth:
-11
Growth Rate:
-275.00%
Total runs:
3
Run Growth:
-12
Growth Rate:
-400.00%
Total runs:
2
Run Growth:
-2
Growth Rate:
-100.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%