Instructions to use prithivMLmods/LZO-1-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prithivMLmods/LZO-1-Preview 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("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("prithivMLmods/LZO-1-Preview") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
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# **LZO-1-Preview**
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> LZO-1-Preview (Lossless-Zoom-Operator) is an experimental adapter for black-forest-lab’s FLUX.1-Kontext-dev. It is an experimental LoRA designed to zoom into a defined object frame within an image without altering the object's position, maintaining strict center-staged positioning. The model was trained on 550 image pairs (225 original “start” images and 225 “end” images). Synthetic result nodes were generated using Gemini 2.5 Flash Image Preview from Google and annotated with DeepCaption-VLA-7B.
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# **LZO-1-Preview(experimental)**
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> LZO-1-Preview (Lossless-Zoom-Operator) is an experimental adapter for black-forest-lab’s FLUX.1-Kontext-dev. It is an experimental LoRA designed to zoom into a defined object frame within an image without altering the object's position, maintaining strict center-staged positioning. The model was trained on 550 image pairs (225 original “start” images and 225 “end” images). Synthetic result nodes were generated using Gemini 2.5 Flash Image Preview from Google and annotated with DeepCaption-VLA-7B.
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