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README.md

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+---
+tags:
+  - ltx-2
+  - ltx-video
+  - text-to-video
+  - audio-video
+pinned: true
+language:
+  - en
+license: other
+pipeline_tag: text-to-video
+library_name: diffusers
+---
+
+# ltx2-lora2
+
+Trained with the [LTX LoRA Trainer](https://huggingface.co/spaces/ltx-community/ltx2-lora-trainer) — powered by [LTX-2](https://github.com/Lightricks/LTX-2).
+
+This is a **Text-to-Video LoRA** fine-tuned from [`ltx-2.3-22b-dev.safetensors`](https://huggingface.co/Lightricks/LTX-2.3) on custom data.
+
+## Model Details
+
+- **Base Model:** [`ltx-2.3-22b-dev.safetensors`](https://huggingface.co/Lightricks/LTX-2.3)
+- **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](https://github.com/Lightricks/LTX-2).
+
+### 🔌 Using Trained LoRAs in ComfyUI
+
+In order to use the trained LoRA in ComfyUI, follow these steps:
+
+1. Copy your trained LoRA checkpoint (`.safetensors` file) to the `models/loras` folder in your ComfyUI installation.
+2. In your ComfyUI workflow:
+    - Add the "Load LoRA" node to choose your LoRA file
+    - 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](https://github.com/Lightricks/LTX-2).
+
+### Example Prompts
+
+
+
+
+This model inherits the license of the base model ([`ltx-2.3-22b-dev.safetensors`](https://huggingface.co/Lightricks/LTX-2.3)).
+
+## Acknowledgments
+
+- Base model: [Lightricks](https://huggingface.co/Lightricks/LTX-2)
+- Trainer: [LTX-2](https://github.com/Lightricks/LTX-2)

lora_weights_step_02000.safetensors

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