---
title: TeleStyleV2-Qwen-Image-Edit-2511-bf16
canonical_url: "https://www.modelscope.cn/models/mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16"
md_url: "https://www.modelscope.cn/models/mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16.md"
repository: mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16
last_updated: 2026-06-25
license: apache-2.0
pipeline_tag: image-to-image
tasks:
  - image-to-image
base_model:
  - Qwen/Qwen-Image-Edit-2511
  - Tele-AI/TeleStyleV2
base_model_relation: finetune
parameters: 28.7B
tensor_type:
  - BF16
library_name:
  - pytorch
  - mlx
  - diffusers
  - safetensors
frameworks:
  - pytorch
downloads: 574
stars: 4
tags:
  - image-to-image
  - style-transfer
  - image-editing
  - qwen-image-edit
  - mlx
  - diffusers
---

# TeleStyleV2-Qwen-Image-Edit-2511-bf16

> TeleStyleV2-Qwen-Image-Edit-2511-bf16 - mlx-community 在 ModelScope 开源的模型。TeleStyleV2-Qwen-Image-Edit-2511-bf16

mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16 是 ModelScope 魔搭社区上的 28.7B 参数image-to-image模型，采用 apache-2.0 许可，基于 Qwen/Qwen-Image-Edit-2511、Tele-AI/TeleStyleV2 构建。

- **Repository**: mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16
- **License**: apache-2.0
- **Tasks**: image-to-image
- **Parameters**: 28.7B
- **Base model**: Qwen/Qwen-Image-Edit-2511, Tele-AI/TeleStyleV2
- **Tags**: image-to-image, style-transfer, image-editing, qwen-image-edit, mlx, diffusers
- **Downloads**: 574
- **Stars**: 4
- **Last updated**: 2026-06-25

Source: https://www.modelscope.cn/models/mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16

---

# TeleStyleV2-Qwen-Image-Edit-2511-bf16

A **ready-to-run, pre-fused** checkpoint of [Tele-AI/TeleStyleV2](https://github.com/Tele-AI/TeleStyleV2)
for **content-preserving image style transfer**, built on
[Qwen/Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511).

TeleStyleV2 ships only LoRA adapters. This repo has those adapters **merged into the base
transformer at scale 1.0**, exactly as the reference app does — so no LoRA loading is needed:

- `diffusers-TeleStyleV2-QIE-2511-Lora` (the style-transfer LoRA)
- `QIE-2511-Lightning-4steps` (the Lightning / Distribution-Matching-Distillation LoRA → 4-step inference)

Everything else (`vae/`, `text_encoder/` = Qwen2.5-VL-7B, `processor/`, `tokenizer/`, `scheduler/`)
is the unmodified Qwen-Image-Edit-2511 base, so the repo is a drop-in self-contained snapshot.

## What it does

Given a **content** image and a **style** image, it transfers the style of the style image onto the
content image while preserving the content — across realistic/stylized pairs (R+R, R+S, S+R, S+S). It
also serves plain instruction edits (content image only). Image 1 = content, Image 2 = style; there is
no role token, the fused LoRA learned the order.

## Usage (diffusers)

```python
import torch
from diffusers import QwenImageEditPlusPipeline
from PIL import Image

pipe = QwenImageEditPlusPipeline.from_pretrained(
    "mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16", torch_dtype=torch.bfloat16
).to("cuda")

content = Image.open("content.png")
style = Image.open("style.png")
image = pipe(
    image=[content, style],
    prompt="Style Transfer the style of Figure 2 to Figure 1, and keep the content "
           "and characteristics of Figure 1.",
    num_inference_steps=4,        # Lightning/DMD
    true_cfg_scale=1.0,           # DMD: no CFG
    generator=torch.manual_seed(123),
).images[0]
image.save("out.png")
```

## Usage (MLX / Apple Silicon)

Consumable by [qwen-image-edit-swift](https://github.com/xocialize/qwen-image-edit-swift) (the
`MLXTeleStyle` package, an MLXEngine `imageEdit` surface with a `styleTransfer` mode). The Swift port
reads this diffusers snapshot directly. ~60 GB resident in bf16 (20B DiT + Qwen2.5-VL-7B + fp32 VAE);
4-step DMD inference.

## License & credits

Apache-2.0. Built on [Tele-AI/TeleStyleV2](https://huggingface.co/Tele-AI/TeleStyleV2) (the LoRAs)
and [Qwen/Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511) (the base). Merge
performed with `diffusers` `fuse_lora(scale=1.0)`. Please cite the TeleStyleV2 technical report
([arXiv:2601.20175](https://arxiv.org/abs/2601.20175)).