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--- |
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tags: |
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- text-to-image |
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- lora |
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- diffusers |
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- template:diffusion-lora |
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widget: |
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- text: 'frosted GC, a pristine white jar, adorned with a silver lid, is adorned with the words "Spirulina" in bold black lettering. The jar is set against a light blue backdrop, creating a stark contrast to the jars contents. A barcode is visible on the jar, adding a pop of color to the composition.' |
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output: |
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url: images/FG1.png |
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- text: 'frosted GC, A medium shot of a white jar with a yellow lid. The jar has the words "Yellow" and "Fish Oil Bottle Mockup" written on it in black letters. There is a white background behind the jar.' |
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output: |
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url: images/FG2.png |
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- text: 'frosted GC, a small, gray bottle with a black cap is seen against a stark white backdrop. The bottles label, "Cellular Nutrition mitopure" is prominently displayed in the center of the frame, with the words "Time-line" written in white font on the right side of the bottle. The label also includes the number "60" and "50" in the bottom left corner.' |
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output: |
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url: images/FG3.png |
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base_model: black-forest-labs/FLUX.1-dev |
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instance_prompt: frosted GC |
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license: creativeml-openrail-m |
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--- |
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# Flux.1-Dev-Frosted-Container-LoRA |
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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.1-Dev-Frosted-Container-LoRA** |
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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 | 14 & 2200 | |
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| Epoch | 10 | Save Every N Epochs | 1 | |
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Labeling: florence2-en(natural language & English) |
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Total Images Used for Training : 16 |
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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.1-Dev-Frosted-Container-LoRA" |
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trigger_word = "frosted GC" |
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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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# Other Sample Image |
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## Trigger words |
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You should use `frosted GC` 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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[Download](/prithivMLmods/Flux.1-Dev-Frosted-Container-LoRA/tree/main) them in the Files & versions tab. |
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