---
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: a Komaru cat sitting in a box of corn on top of a couch
  output:
    url: images/71_.png
- text: a Komaru cat laying on its back on the wooden floor
  output:
    url: images/76_.png
- text: a person holding a Komaru cat in their hands
  output:
    url: images/hack337_00005_.jpg
- text: a Komaru cat sitting atop a cardboard box
  output:
    url: images/hack337_00004_.png
- text: a Komaru cat sitting atop a wooden drawer, with a wall on the right side
  output:
    url: images/._00001_.png
- text: >-
    a Komaru cat wearing a pink hat with ears, sitting on a wooden surface with
    a blurred background
  output:
    url: images/hack337_00002_.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Komaru
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
---
# Komaru

<Gallery />

## Model description 

Komaru, a charming Kincalow cat, is the star of this LoRa. Follow her adventures and cuteness on her human&#39;s Instagram: @mugimeshi323

## Trigger words

You should use `Komaru` to trigger the image generation.


## Download model

Weights for this model are available in Safetensors format.

[Download](/Hack337/flux-lora-Komaru/tree/main) them in the Files & versions tab.

## 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.bfloat16).to('cuda')
pipeline.load_lora_weights('Hack337/flux-lora-Komaru', weight_name='komaru')
image = pipeline('a Komaru cat sitting in a box of corn on top of a couch, with a white cloth draped over it').images[0]
image.save("my_image.png")
```

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)