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Quantumbraid/ltx2-lora2

sourceHugging Faceotherupdated 2mo agoView on Hugging Face
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ltx2-lora2

Trained with the LTX LoRA Trainer — powered by LTX-2.

This is a Text-to-Video LoRA fine-tuned from `ltx-2.3-22b-dev.safetensors` on custom data.

Model Details

  • —Base Model: `ltx-2.3-22b-dev.safetensors`
  • —LoRA type: Text-to-Video LoRA
  • —Training Type: LoRA fine-tuning
  • —Training Steps: 2000
  • —Learning Rate: 0.0001
  • —Batch Size: 1

Sample Outputs

Usage

🧨 Diffusers

LTX-2.3 support is currently on the diffusers main branch: pip install git+https://github.com/huggingface/diffusers.git
python
import torch
from diffusers import LTX2Pipeline
from diffusers.pipelines.ltx2.export_utils import encode_video
from diffusers.pipelines.ltx2.utils import DEFAULT_NEGATIVE_PROMPT

pipe = LTX2Pipeline.from_pretrained(
    "diffusers/LTX-2.3-Diffusers", torch_dtype=torch.bfloat16
)
pipe.enable_model_cpu_offload()

# Load this LoRA
pipe.load_lora_weights("Quantumbraid/ltx2-lora2", weight_name="lora_weights_step_02000.safetensors", adapter_name="lora")
pipe.set_adapters("lora", 1.0)

video, audio = pipe(
    prompt="<your prompt>",
    negative_prompt=DEFAULT_NEGATIVE_PROMPT,
    width=768, height=512, num_frames=49, frame_rate=25.0,
    num_inference_steps=30, guidance_scale=4.0,
    output_type="np", return_dict=False,
)
encode_video(video[0], fps=25.0, output_path="output.mp4")

For the full reference implementation and ComfyUI workflows, see the official LTX-2 repository.

🔌 Using Trained LoRAs in ComfyUI

In order to use the trained LoRA in ComfyUI, follow these steps:

  1. 1.Copy your trained LoRA checkpoint (.safetensors file) to the models/loras folder in your ComfyUI installation.
  2. 2.In your ComfyUI workflow:
  3. 3.Add the "Load LoRA" node to choose your LoRA file
  4. 4.Connect it to the "Load Checkpoint" node to apply the LoRA to the base model

You can find reference Text-to-Video (T2V) and Image-to-Video (I2V) workflows in the official LTX-2 repository.

Example Prompts

This model inherits the license of the base model (`ltx-2.3-22b-dev.safetensors`).

Acknowledgments