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---
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- 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.'
output:
url: images/FG1.png
- 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.'
output:
url: images/FG2.png
- 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.'
output:
url: images/FG3.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: frosted GC
license: creativeml-openrail-m
---
# Flux.1-Dev-Frosted-Container-LoRA
<Gallery />
**The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.**
## Model description
**prithivMLmods/Flux.1-Dev-Frosted-Container-LoRA**
Image Processing Parameters
| Parameter | Value | Parameter | Value |
|---------------------------|--------|---------------------------|--------|
| LR Scheduler | constant | Noise Offset | 0.03 |
| Optimizer | AdamW | Multires Noise Discount | 0.1 |
| Network Dim | 64 | Multires Noise Iterations | 10 |
| Network Alpha | 32 | Repeat & Steps | 14 & 2200 |
| Epoch | 10 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 16
## Best Dimensions
- 768 x 1024 (Best)
- 1024 x 1024 (Default)
## Setting Up
```python
import torch
from pipelines import DiffusionPipeline
base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Flux.1-Dev-Frosted-Container-LoRA"
trigger_word = "frosted GC"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
```
# Other Sample Image
## Trigger words
You should use `frosted GC` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/prithivMLmods/Flux.1-Dev-Frosted-Container-LoRA/tree/main) them in the Files & versions tab.
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