README.md

---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev/blob/main/LICENSE.md
language:
- en
library_name: diffusers
base_model:
- black-forest-labs/FLUX.1-Krea-dev
pipeline_tag: text-to-image
widget:
- text: a frog holding a sign that says hello world
  output:
    url: output1.png
- text: a pig holding a sign that says hello world
  output:
    url: output2.png
- text: a wolf holding a sign that says hello world
  output:
    url: output3.png
- text: >-
    cute anime girl with massive fluffy fennec ears and a big fluffy tail blonde
    messy long hair blue eyes wearing a maid outfit with a long black gold leaf
    pattern dress and a white apron mouth open holding a fancy black forest cake
    with candles on top in the kitchen of an old dark Victorian mansion lit by
    candlelight with a bright window to the foggy forest and very expensive
    stuff everywhere
  output:
    url: workflow-embedded-demo1.png
- text: >-
    on a rainy night, a girl holds an umbrella and looks at the camera. The rain
    keeps falling.
  output:
    url: workflow-embedded-demo2.png
- text: drone shot of a volcano erupting with a pig walking on it
  output:
    url: workflow-embedded-demo3.png
tags:
- gguf-node
- gguf-connector
---
# **gguf quantized version of krea**
- run it straight with `gguf-connector`
- opt a `gguf` file in the current directory to interact with by:
```
ggc k
```
>
>GGUF file(s) available. Select which one to use:
>
>1. flux-krea-lite-q2_k.gguf
>2. flux-krea-lite-q4_0.gguf
>3. flux-krea-lite-q8_0.gguf
>
>Enter your choice (1 to 3): _
>
note: try experimental lite model with 8-step operation; save up to 70% loading time

![screenshot](https://raw.githubusercontent.com/calcuis/gguf-pack/master/k4.png)

- run it with diffusers (see example inference below)
```py
import torch
from transformers import T5EncoderModel
from diffusers import FluxPipeline, GGUFQuantizationConfig, FluxTransformer2DModel

model_path = "https://huggingface.co/calcuis/krea-gguf/blob/main/flux1-krea-dev-q2_k.gguf"
transformer = FluxTransformer2DModel.from_single_file(
    model_path,
    quantization_config=GGUFQuantizationConfig(compute_dtype=torch.bfloat16),
    torch_dtype=torch.bfloat16,
    config="callgg/krea-decoder",
    subfolder="transformer"
)

text_encoder = T5EncoderModel.from_pretrained(
    "chatpig/t5-v1_1-xxl-encoder-fp32-gguf",
    gguf_file="t5xxl-encoder-fp32-q2_k.gguf",
    torch_dtype=torch.bfloat16
    )

pipe = FluxPipeline.from_pretrained(
    "callgg/krea-decoder",
    transformer=transformer,
    text_encoder_2=text_encoder,
    torch_dtype=torch.bfloat16
    )
pipe.enable_model_cpu_offload() # could change it to cuda if you have good gpu

prompt = "a pig holding a sign that says hello world"
image = pipe(
    prompt,
    height=1024,
    width=1024,
    guidance_scale=2.5,
).images[0]
image.save("output.png")
```

<Gallery />

## **run it with gguf-node via comfyui**
- drag **krea** to > `./ComfyUI/models/diffusion_models`
- drag **clip-l-v2 [[248MB](https://huggingface.co/calcuis/kontext-gguf/blob/main/clip_l_v2_fp32-f16.gguf)], t5xxl [[2.75GB](https://huggingface.co/calcuis/kontext-gguf/blob/main/t5xxl_fp32-q4_0.gguf)]** to > `./ComfyUI/models/text_encoders`
- drag **pig [[168MB](https://huggingface.co/calcuis/kontext-gguf/blob/main/pig_flux_vae_fp32-f16.gguf)]** to > `./ComfyUI/models/vae`

![screenshot](https://raw.githubusercontent.com/calcuis/comfy/master/krea.png)

### **reference**
- base model from [black-forest-labs](https://huggingface.co/black-forest-labs)
- for model merge details, see [sayakpaul](https://huggingface.co/sayakpaul/FLUX.1-merged)
- diffusers from [huggingface](https://github.com/huggingface/diffusers)
- comfyui from [comfyanonymous](https://github.com/comfyanonymous/ComfyUI)
- gguf-node ([pypi](https://pypi.org/project/gguf-node)|[repo](https://github.com/calcuis/gguf)|[pack](https://github.com/calcuis/gguf/releases))
- gguf-connector ([pypi](https://pypi.org/project/gguf-connector))