Downloads · 30 days
36
3% of all-time downloads
prithivMLmods/LZO-1-Preview
LZO-1-Preview is a image-to-image model from prithivMLmods. Use it when you need one image transformed into another. It is set up for diffusers. The card lists the license as other.
Downloads · 30 days
36
3% of all-time downloads
All-time downloads
1K
Public
Repo size
615 MB
Likes
2
Public
Click a slice to open those files.
.safetensors613 MB · 100%
From the Hugging Face model README

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 (275 original “start” images and 275 “end” images). Synthetic result nodes were generated using Gemini 2.5 Flash Image Preview from Google and annotated with DeepCaption-VLA-7B.
[!note] [photo content], zoom in on the specified [face/object/region close-up], enhancing resolution and detail while preserving sharpness, realism, and original context. Maintain natural proportions and background continuity around the zoomed area.
[photo content], zoom in on the specified [face close-up], enhancing resolution and detail while preserving sharpness, realism, and original context. Maintain natural proportions and background continuity around the zoomed area.
| Example 1 | Example 2 |
|---|---|
![]() | ![]() |
This is an experimental model and may generate sub-optimal results at times. Make sure the uploaded image is of good quality, as poor-quality input images may produce artifacts. Also, ensure that the input includes a proper prompt for optimal results. The model is optimized and works well on human face cards, anime images, automotive images, and sports action images.
| Setting | Value |
|---|---|
| Module Type | Adapter |
| Base Model | FLUX.1 Kontext Dev - fp8 |
| Trigger Words | [photo content], zoom in on the specified [face/object/region close-up], enhancing resolution and detail while preserving sharpness, realism, and original context. Maintain natural proportions and background continuity around the zoomed area. |
| Image Processing Repeats | 50 |
| Epochs | 30 |
| Save Every N Epochs | 1 |
Labeling: DeepCaption-VLA-7B(natural language & English)
Total Images Used for Training : 550 Image Pairs (275 Start, 275 End)
Synthetic Result Node generated by gemini-2.5-flash-image-preview
| Setting | Value |
|---|---|
| Seed | - |
| Clip Skip | - |
| Text Encoder LR | 0.00001 |
| UNet LR | 0.00005 |
| LR Scheduler | constant |
| Optimizer | AdamW8bit |
| Network Dimension | 64 |
| Network Alpha | 32 |
| Gradient Accumulation Steps | - |
| Setting | Value |
|---|---|
| Shuffle Caption | - |
| Keep N Tokens | - |
| Setting | Value |
|---|---|
| Noise Offset | 0.03 |
| Multires Noise Discount | 0.1 |
| Multires Noise Iterations | 10 |
| Conv Dimension | - |
| Conv Alpha | - |
| Batch Size | - |
| Steps | 3900 (Low(700)) |
| Sampler | euler |
You should use [photo content] to trigger the image generation.
You should use zoom in on the specified [face/object/region close-up] to trigger the image generation.
You should use enhancing resolution and detail while preserving sharpness to trigger the image generation.
You should use realism to trigger the image generation.
You should use and original context. Maintain natural proportions and background continuity around the zoomed area. to trigger the image generation.
Download them in the Files & versions tab.