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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: CONTTOK
widget:
- text: >-
    This image showcases a modern, two-story house with a contemporary
    architectural design. The structure features a clean, white facade
    complemented by stone-textured accents that add a touch of natural elegance.
    Large windows allow ample natural light to filter into the interiors, while
    sleek, horizontal railings adorn the spacious balconies and rooftop terrace.
    The house is surrounded by lush greenery, including potted plants and a
    well-maintained garden. The front entrance is marked by wooden doors, and a
    carport is neatly integrated into the layout, providing shelter for
    vehicles. Warm lighting fixtures on the exterior walls create a welcoming
    ambiance, enhancing the house's visual appeal during the evening. This
    design offers a luxurious yet cozy atmosphere, ideal for a family residence
    with five bedrooms and three bathrooms.
  output:
    url: images/example_voziii3sc.png

---

# Flux.1 Dev Lora Container

<!-- <Gallery /> -->

Trained on Replicate using:

https://replicate.com/ostris/flux-dev-lora-trainer/train


## Trigger words
You should use `CONTTOK` to trigger the image generation.


## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
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('KalaniP/flux.1-dev-lora-container', weight_name='lora.safetensors')
image = pipeline('your prompt').images[0]
```

For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)