Instructions to use prithivMLmods/Flux-Polaroid-Plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prithivMLmods/Flux-Polaroid-Plus with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("prithivMLmods/Flux-Polaroid-Plus") prompt = "Polaroid Collage, a collage of photographs of the New York City is displayed on a white surface. The photographs are arranged in a grid-like pattern, with a variety of buildings and skyscrapers visible. The buildings are lit up, creating a stark contrast against the blue sky. The photograph is taken from a low angle, adding a touch of depth to the composition." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update README.md
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README.md
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<Gallery />
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## Trigger words
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You should use `Polaroid Collage` to trigger the image generation.
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## Download model
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Weights for this model are available in Safetensors format.
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<Gallery />
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**The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.**
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## Model description
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**prithivMLmods/Flux-Polaroid-Plus**
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Image Processing Parameters
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| Parameter | Value | Parameter | Value |
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|---------------------------|--------|---------------------------|--------|
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| LR Scheduler | constant | Noise Offset | 0.03 |
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| Optimizer | AdamW | Multires Noise Discount | 0.1 |
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| Network Dim | 64 | Multires Noise Iterations | 10 |
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| Network Alpha | 32 | Repeat & Steps | 23 & 3300 |
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| Epoch | 17 | Save Every N Epochs | 1 |
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Labeling: florence2-en(natural language & English)
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Total Images Used for Training : 24
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## Best Dimensions
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- 768 x 1024 (Best)
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- 1024 x 1024 (Default)
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## Setting Up
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```python
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import torch
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from pipelines import DiffusionPipeline
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base_model = "black-forest-labs/FLUX.1-dev"
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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lora_repo = "prithivMLmods/Flux-Polaroid-Plus"
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trigger_word = "Polaroid Collage"
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pipe.load_lora_weights(lora_repo)
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device = torch.device("cuda")
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pipe.to(device)
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```
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## Trigger words
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You should use `Polaroid Collage` to trigger the image generation.
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## Download model
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Weights for this model are available in Safetensors format.
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