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---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
language:
- en
tags:
- flux
- diffusers
- lora
- replicate
base_model: "black-forest-labs/FLUX.1-dev"
pipeline_tag: text-to-image
instance_prompt: sectorSaveBox
---
# SectorSaveBox
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers, ComfyUI, or Replicate.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: [ostris/flux-dev-lora-trainer](https://replicate.com/ostris/flux-dev-lora-trainer/train)
## Trigger words
You should use `sectorSaveBox` to trigger the image generation.
## Prompting Tips
You can combine it with environments, lighting styles, or action verbs. Examples:
- `sectorSaveBox, on a white wall, close-up product photo`
- `sectorSaveBox, a person holding the device indoors`
- `sectorSaveBox, studio-lit product showcase`
## Run this LoRA with an API using Replicate
```py
import replicate
input = {
"prompt": "sectorSaveBox",
"lora_weights": "https://huggingface.co/KAPPA66/sectorSaveBox/resolve/main/lora.safetensors"
}
output = replicate.run(
"black-forest-labs/flux-dev-lora",
input=input
)
for index, item in enumerate(output):
with open(f"output_{index}.webp", "wb") as file:
file.write(item.read())
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('KAPPA66/sectorSaveBox', weight_name='lora.safetensors')
image = pipeline('sectorSaveBox').images[0]
## Training details
- Steps: 1000
- Learning rate: 0.0004
- LoRA rank: 16
## Contribute your own examples
Use the [community tab](https://huggingface.co/KAPPA66/sectorSaveBox/discussions) to share images you've made with this LoRA.
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