---
license: apache-2.0
language:
  - en
tags:
  - text-to-video
  - image-to-video
  - lora
  - safetensors
  - video-generation
  - wan
  - wan2.1
  - diffusion-pipe
  - musubi-tuner
  - identity
base_model: Wan-AI/Wan2.1-I2V-14B-720P
base_model_relation: adapter
library_name: diffusers
pipeline_tag: image-to-video
instance_prompt: "ohwx"
---

# WAN 2.1 LoRA — `ohwx`

A personalized LoRA (Low-Rank Adaptation) trained on **WAN 2.1 14B** for generating video content with a specific identity.
Works with both **Image-to-Video** and **Text-to-Video** WAN 2.1 pipelines.

Trained using dual-mode Musubi Tuner (high + low noise models → single LoRA file).

## Quick Start

### Direct Download URL
```
https://huggingface.co/fwwrsd/ohwx-wan-lora/resolve/main/lora.safetensors
```

### ComfyUI Setup
1. Download `lora.safetensors` → place in `ComfyUI/models/loras/`
2. Use **WAN LoRA Loader** node
3. Set trigger word: `ohwx`

### Load Directly from URL (ComfyUI)
Many LoRA loader nodes support loading directly from a HuggingFace URL:
```
https://huggingface.co/fwwrsd/ohwx-wan-lora/resolve/main/lora.safetensors
```
No download needed — ComfyUI caches it automatically.

### Download via Command Line
```bash
# wget
wget https://huggingface.co/fwwrsd/ohwx-wan-lora/resolve/main/lora.safetensors -O lora_ohwx.safetensors

# curl
curl -L https://huggingface.co/fwwrsd/ohwx-wan-lora/resolve/main/lora.safetensors -o lora_ohwx.safetensors

# huggingface-cli
huggingface-cli download fwwrsd/ohwx-wan-lora lora.safetensors
```

## Recommended Settings

| Parameter | Image-to-Video | Text-to-Video |
|-----------|---------------|---------------|
| LoRA Strength (motion) | 0.3 — 0.4 | 0.3 — 0.4 |
| LoRA Strength (identity) | 0.85 — 0.95 | 0.85 — 0.95 |
| CFG Scale | 0.52 | 1.0 |
| Steps | 30 — 50 | 30 — 50 |
| Sampler | euler / dpmpp_2m | euler / dpmpp_2m |

**Trigger word:** `ohwx` — include in your prompt to activate the LoRA.

## Training Details

| Parameter | Value |
|-----------|-------|
| Base Model | `Wan-AI/Wan2.1-I2V-14B-720P` |
| Training Method | Musubi Tuner (dual-mode: high + low noise) |
| LoRA Rank | 16 |
| Learning Rate | 1e-4 |
| LR Scheduler | cosine with 5% warmup |
| Optimizer | adamw + LoRA+ (ratio=4) |
| Training Steps | ~unknown |
| Epochs | unknown |
| Resolution | 1024px |
| Dataset Size | unknown images |
| Captions | No (photos only) |
| Precision | fp16 (LoRA) + fp8 (base model) |
| Preset | standard |
| Created | 2026-06-20 |
| GPU | NVIDIA H200 SXM 141GB |

## Architecture

This is a **dual-mode LoRA** trained with `--timestep_boundary 875`:
- **High-noise model** (timesteps > 875): Handles initial structure and motion
- **Low-noise model** (timesteps ≤ 875): Handles fine details and identity

Both models are trained simultaneously and packed into a single `.safetensors` file.
Compatible with any WAN 2.1 workflow that supports LoRA.

## License

Apache 2.0 — free for personal and commercial use.

---
*Trained with [NanoBanana LoRA Bot](https://t.me/LoraDatasetBot) on RunPod*