Kasnol/FLUX.1-dev-LoRA-AsianMaleAthleticModel
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Kasnol
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GRID-6X : Layout for Seamless Image Assembly 🔥
🪨Demo: https://huggingface.co/spaces/prithivMLmods/GRID-6X
🪨Doc / Blog: https://huggingface.co/blog/prithivMLmods/grid-6x
In the `infer` function:
```python
grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y))
for i, img in enumerate(result.images[:num_images]):
grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height))
```
1. **Image Initialization**: `grid_img` is a blank canvas that will hold the images in a grid format.
2. **Image Placement**: Images are pasted onto the canvas using a loop:
- **Horizontal Position**: `(i % grid_size_x) * width` calculates the x-coordinate.
- **Vertical Position**: `(i // grid_size_x) * height` calculates the y-coordinate.
1. **Grid Size Selection**: The user selects the grid size from options like "2x1", "1x2", "2x2", "2x3", "3x2", and "1x1". Each option corresponds to the arrangement of images:
- **2x1**: 2 images in a single row
- **1x2**: 1 image in two rows (column layout)
- **2x2**: 2 rows with 2 images each
- **2x3**: 2 rows with 3 images each
- **3x2**: 3 rows with 2 images each
- **1x1**: A single image (default)
2. **Image Generation**: Based on the grid size selection, the app calculates the number of images to generate. For example:
- If the grid size is "2x2", the app generates 4 images.
- For "3x2", it generates 6 images.
-> Each option arranges images accordingly, providing flexibility in viewing multiple images in one output.
-> Added both of these spaces that support the GRID functionality Layout for Seamless Image Assembly :
----------
🔥IMAGINEO-4K: https://huggingface.co/spaces/prithivMLmods/IMAGINEO-4K
🔥GRID-6X: https://huggingface.co/spaces/prithivMLmods/GRID-6X
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.@prithivMLmods 🤗
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We just released a paper (NeuZip) that compresses VRAM in a lossless manner to run larger models. This should be particularly useful when VRAM is insufficient during training/inference. Specifically, we look inside each floating number and find that the exponents are highly compressible (as shown in the figure below).
Read more about the work at https://huggingface.co/papers/2410.20650
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stabilityai/stable-diffusion-3.5-large
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