Instructions to use lightx2v/Qwen-Image-Edit-2511-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Qwen-Image-Edit-2511-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit-2511", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lightx2v/Qwen-Image-Edit-2511-Lightning") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Diffusion Single File
How to use lightx2v/Qwen-Image-Edit-2511-Lightning with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
π Documentation Enhancement Suggestion
π Documentation Enhancement Suggestion
This observation was generated by Crovia β the AI transparency observation layer.
Crovia does not accuse or judge. It observes publicly available information and suggests improvements.
π Quick Stats
| Metric | Value |
|---|---|
| Source | huggingface |
| Downloads | 349364 |
| Likes | 363 |
| Last Updated | 2026-02-13 |
π» Ready-to-Use Code
from transformers import AutoModel, AutoTokenizer
model_id = "lightx2v/Qwen-Image-Edit-2511-Lightning"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModel.from_pretrained(model_id)
# Example usage
inputs = tokenizer("Hello, world!", return_tensors="pt")
outputs = model(**inputs)
π Citation
If you use this model, please cite:
@misc {lightx2v_Qwen_Image_Edit_2511_Lightning_2026,
author = {lightx2v},
title = {lightx2v/Qwen-Image-Edit-2511-Lightning},
year = {2026},
url = {https://huggingface.co/lightx2v/Qwen-Image-Edit-2511-Lightning},
note = {Accessed via CROVIA transparency registry}
}
βοΈ EU AI Act Compliance Checklist
- Training data disclosed
- License clearly stated
- Intended use documented
- Model limitations documented
- Evaluation metrics provided
- Bias/fairness analysis
π Training Data Transparency
Training Data Status: Documentation not found
No training data section was observed in the public model card.
This is an observation, not an accusation. Many valid reasons exist for this status.
If you'd like to improve documentation, consider adding:
- Dataset names and versions used
- Data collection methodology
- Preprocessing steps applied
- Known limitations
This may help users understand your model better and prepare for upcoming transparency requirements (e.g., EU AI Act).
Enhancement generated by CROVIA Β· Package ID: 3c7a919218f1
Generated at: 2026-02-13T17:06:57.621928Z
This suggestion was generated by Crovia β the AI transparency observation layer.
Crovia does not accuse or judge. It observes publicly available information and suggests documentation improvements.
If this suggestion is helpful, consider adding the recommended sections to your model card.
If not applicable, feel free to close this discussion.
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