---
title: Manjushya
canonical_url: "https://www.modelscope.ai/models/krznun/Manjushya"
md_url: "https://www.modelscope.ai/models/krznun/Manjushya.md"
repository: krznun/Manjushya
last_updated: 2026-03-18
license: "Apache License 2.0"
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
base_model:
  - Qwen/Qwen-Image-2512
base_model_relation: adapter
parameters: 147.5M
tensor_type:
  - BF16
library_name:
  - lora
  - safetensors
  - pytorch
frameworks:
  - Pytorch
supports_inference: txt2img
downloads: 12
stars: 0
tags:
  - LoRA
  - text-to-image
---

# Manjushya

> Manjushya - An open-source model by krznun on ModelScope. Trigger word : m@njushya art of <xyz>

krznun/Manjushya is a 147.5M-parameter text-to-image-synthesis model on ModelScope. licensed under Apache License 2.0. derived from Qwen/Qwen-Image-2512. and supports online inference (txt2img).

- **Repository**: krznun/Manjushya
- **License**: Apache License 2.0
- **Tasks**: text-to-image-synthesis
- **Parameters**: 147.5M
- **Base model**: Qwen/Qwen-Image-2512
- **Online inference**: txt2img
- **Tags**: LoRA, text-to-image
- **Downloads**: 12
- **Stars**: 0
- **Last updated**: 2026-03-18

Source: https://www.modelscope.ai/models/krznun/Manjushya

---

### You are viewing the default Readme template as no detailed model-card was provided by the model’s contributors. You can access the model files in the "Files and versions" tab.
#### Model files may be downloaded with ModelScope SDK or through git clone directly.

Download with ModelScope’s Python SDK
```bash
#Install ModelScope
pip install modelscope
```
```python
#Download with ModelScope’s Python SDK
from modelscope import snapshot_download
model_dir = snapshot_download('krznun/Manjushya')
```
Download with Git clone
```
git clone https://www.modelscope.ai/krznun/Manjushya.git
```

<p style="color: lightgrey;">If you are a contributor to this model, we invite you to promptly update the model card content according to <a href="https://www.modelscope.ai/docs/contribute/model-integration" style="color: lightgrey; text-decoration: underline;">the model contribution documentation</a>.</p>
