---
license: apache-2.0
base_model:
- Lightricks/LTX-2.3
tags:
- video-generation
- lora
- ic-lora
- ltx-video
- camera-motion
- lightricks
---
# LTX-Video 2.3 22B — IC-LoRA: Cameraman v1
A fine-tuned In-Context LoRA (IC-LoRA) adapter for LTX-Video 2.3 (22B),
trained to replicate camera movements from a reference video.
## Example ComfyUI workflow
You can find a ComfyUI workflow example here: https://huggingface.co/datasets/Cseti/ComfyUI-Workflows/blob/main/ltx/2.3/ic-lora-cameraman/README.md
## Example outputs
Each video shows the reference (left) and generated output (right) side by side.
## How It Works
During inference you provide:
- A **reference video** that carries the desired camera motion
- A **text prompt** describing the scene to generate
The model transfers the camera behavior from the reference into the generated
output. No trigger word is required.
## Training Details
| Parameter | Value |
|---|---|
| Base model | LTX-Video 2.3 (22B) |
| Training framework | ltx-trainer (Lightricks) |
| Training strategy | IC-LoRA (video_to_video) |
| Best checkpoint | step 10,500 |
| LoRA rank / alpha | 32 / 32 |
| Target modules | attn1, attn2 (to_k/q/v/out), ff.net.0.proj, ff.net.2 |
| Learning rate | 1e-4 (linear decay) |
| Mixed precision | bf16 |
| Batch size | 1 (gradient checkpointing enabled) |
| Training dataset | 77 video pairs |
| Resolution buckets | 768x512x57; 768x512x89; 768x512x121 |
| First frame conditioning | 0.2 |
### Dataset
77 video pairs annotated by camera motion type, balanced to up to 15 samples
per motion component. Some compound motions (e.g. zoom_in + tilt_up, orbit_cw + pan_left) are also represented.
| Motion | Samples |
|---|---|
| zoom_in | 15 |
| zoom_out | 15 |
| tilt_up | 15 |
| tilt_down | 9 |
| pan_left | 15 |
| pan_right | 15 |
| orbit_cw | 15 |
| orbit_ccw | 15 |
## Usage
Requires the [ltx-trainer](https://github.com/Lightricks/LTX-Video) repo and its dependencies.
```bash
uv run python -m ltx_pipelines.ic_lora \
--distilled-checkpoint-path /path/to/ltx-2.3-22b-distilled.safetensors \
--spatial-upsampler-path /path/to/spatial_upsampler.safetensors \
--gemma-root /path/to/gemma \
--lora lora_weights_step_10500.safetensors 0.8 \
--video-conditioning /path/to/reference.mp4 1.0 \
--prompt "Your scene description here" \
--width 768 --height 512 --num-frames 97 \
--output-path output.mp4
```
- `--video-conditioning`: reference video carrying the camera motion to replicate, followed by conditioning strength
- `--lora`: path to this LoRA followed by strength (0.7–1.0 recommended)
- No trigger word needed
## Tips
- If the camera motion transfer feels too subtle, explicitly describe the desired
movement in the prompt. This can strengthen the effect.
## Limitations
- First experimental IC-LoRA checkpoint — results may vary
- Complex compound motions may not transfer reliably
- Only tested with I2V (image-to-video) conditioning — T2V mode is untested
## License
Apache 2.0