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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: imtiyaz
widget:
- text: >-
Photo of imtiyaz looking slim and bright sitting in office and working on
laptop
output:
url: images/example_e2k0bg9pg.png
- text: >-
image of imtiyaz in black shirt , outdoor with vibrant look and pose ,
looking like model
output:
url: images/example_23qi40d4c.png
- text: >-
Create a high-quality portrait of a young man imtiyaz with short dark hair
and light beard, wearing a stylish leather jacket and sunglasses. The scene
has a natural outdoor setting with greenery in the background, warm
sunlight, and a confident expression. Capture sharp details and a stylish,
casual look.
output:
url: images/example_g59sh2df5.png
- text: >-
Generate a high-resolution portrait of a young man imtiyaz with a confident,
polished look, wearing a well-fitted blazer over a casual shirt, no tie.
Background: an urban cityscape with soft bokeh lights, capturing an elegant
yet approachable style in warm lighting
output:
url: images/example_oojj87cud.png
- text: >-
Photo of imtiyaz looking slim and bright sitting in office and working on
laptop
output:
url: images/example_38vx0zkg4.png
---
# Imtiyaz
<Gallery />
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
## Trigger words
You should use `imtiyaz` 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('imtiyaz0/imtiyaz', 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)
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