Qwen Edit 2509 Multiple angles
Overview
Highlights
- High-fidelity perspective shifts while maintaining object identity
- Optimized for multi-angle product and object visualization
- Apache-2.0 license ensures flexible commercial integration
- Efficient image-to-image workflow for synthetic data generation
Usage
# Install Hugging Face transformers
pip install transformers torch
# Load model with transformers
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("dx8152/Qwen-Edit-2509-Multiple-angles")
tokenizer = AutoTokenizer.from_pretrained("dx8152/Qwen-Edit-2509-Multiple-angles")
Hugging Face Download
We recommend downloading the model via the Hugging Face CLI or Hub SDK.
Guidance:Before downloading, install huggingface_hub with:
pip install -U huggingface_hub
CLI Download
Download the full repository
huggingface-cli download dx8152/Qwen-Edit-2509-Multiple-angles
Download a single file to a local folder (e.g. config.json into ./dir)
huggingface-cli download dx8152/Qwen-Edit-2509-Multiple-angles config.json --local-dir ./dir
See the official docs for more CLI options
SDK Download
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('dx8152/Qwen-Edit-2509-Multiple-angles')
Git Download
Make sure git-lfs is installed first
git lfs install
git clone https://huggingface.co/dx8152/Qwen-Edit-2509-Multiple-angles
To skip LFS large-file downloads, use:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/dx8152/Qwen-Edit-2509-Multiple-angles
Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.
PyTorch / Transformers Usage
Install Transformers
pip install -U transformers torch
Load the model and run inference
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained('dx8152/Qwen-Edit-2509-Multiple-angles')
tokenizer = AutoTokenizer.from_pretrained('dx8152/Qwen-Edit-2509-Multiple-angles')
Model Download
We recommend downloading the model via the ModelScope CLI or SDK.
Guidance:Before downloading, install ModelScope with:
pip install modelscope
CLI Download
Download the full repository
modelscope download --model dx8152/Qwen-Edit-2509-Multiple-angles
Download a single file to a local folder (e.g. README.md into ./dir)
modelscope download --model dx8152/Qwen-Edit-2509-Multiple-angles README.md --local_dir ./dir
See the docs for more CLI options
SDK Download
# 模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('dx8152/Qwen-Edit-2509-Multiple-angles')
Git Download
Make sure git-lfs is installed first
git lfs install
git clone https://www.modelscope.cn/dx8152/Qwen-Edit-2509-Multiple-angles.git
To skip LFS large-file downloads, use:
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/dx8152/Qwen-Edit-2509-Multiple-angles.git
ModelScope 模型页直接下载模型文件;无需将模型文件放在本站服务器。
Notebook Quickstart
Install the ModelScope library
pip install "modelscope[audio,cv,nlp,multi-modal,science]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
Load the model and run inference
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
p = pipeline('text-generation', 'dx8152/Qwen-Edit-2509-Multiple-angles')
Full Documentation
---
license: apache-2.0
base_model:
- Qwen/Qwen-Image-Edit-2509
pipeline_tag: image-to-image
tags:
- lora
library_name: diffusers
---
import os
from huggingface_hub import InferenceClient
client = InferenceClient(
provider="wavespeed",
api_key=os.environ["HF_TOKEN"],
)
with open("cat.png", "rb") as image_file:
input_image = image_file.read()
output is a PIL.Image object
image = client.image_to_image( input_image, prompt="Turn the cat into a tiger.", model="dx8152/Qwen-Edit-2509-Multiple-angles", ) This model is trained (code-free!) on ModelScope. Thanks to ModelScope team for providing the training infra:https://www.modelscope.cn/aigc/modelTraining
-------
Updated 2025/11/2: Some people mentioned that the model has an unstable consistency issue. I have re-uploaded a version with more training iterations, hoping to fix the consistency problem.
Welcome everyone to use Lora of Qwen-Edit-2509, its performance is very amazing!
There are no trigger words. You can control the camera to move up, down, left, and right, as well as rotate it to the left and right. You can also look down or up. The camera can be changed to a wide-angle or close-up shot.
Online running link: www.runninghub.ai/post/1985311204883243009?inviteCode=rh-v1331
This is a user guide:
YouTube:https://youtu.be/UGdW8W1MqW8
Blibili:https://www.bilibili.com/video/BV1oi1gBBEZV/
“
将镜头向前移动(Move the camera forward.)
将镜头向左移动(Move the camera left.)
将镜头向右移动(Move the camera right.)
将镜头向下移动(Move the camera down.)
将镜头向左旋转45度(Rotate the camera 45 degrees to the left.)
将镜头向右旋转45度(Rotate the camera 45 degrees to the right.)
将镜头转为俯视(Turn the camera to a top-down view.)
将镜头转为广角镜头(Turn the camera to a wide-angle lens.)
将镜头转为特写镜头(Turn the camera to a close-up.)
...
There are many possibilities; you can try them yourself.
”
------
Instructions: Download the lora file to the models/loras folder.
You also need this lora and use them together: https://huggingface.co/lightx2v/Qwen-Image-Lightning/tree/main
For communication/cooperation, you can join the discord group to communicate: https://discord.gg/yVAVa43mWk
If these resources are helpful to you, or if you use them for business purposes, please buy me a coffee. Thank you for supporting original content! PayPal: Daniel8152
!效果图
!效果图2
!效果图3
I saw some people wanted to see a comparison between LoRa and the model's inherent capabilities, so I conducted a test. The trained model is indeed more powerful and intelligent, while the original model already possessed certain abilities. It's very powerful, which is why we love this model, and precisely because of this, we need to explore its potential.
!对比图