feat: support flux.1-krea-dev (#578)

README.md

@@ -15,6 +15,7 @@ Join our user groups on [**Slack**](https://join.slack.com/t/nunchaku/shared_inv
 
 ## News
 
+- **[2025-07-31]** 🚀 **[FLUX.1-Krea-dev](https://www.krea.ai/blog/flux-krea-open-source-release) is now supported!** Check out our new [example script](./examples/flux.1-krea-dev.py) to get started.
 - **[2025-07-13]** 🚀 The official [**Nunchaku documentation**](https://nunchaku.tech/docs/nunchaku/) is now live! Explore comprehensive guides and resources to help you get started.
 - **[2025-06-29]** 🔥 Support **FLUX.1-Kontext**! Try out our [example script](./examples/flux.1-kontext-dev.py) to see it in action! Our demo is available at this [link](https://svdquant.mit.edu/kontext/)!
 - **[2025-06-01]** 🚀 **Release v0.3.0!** This update adds support for multiple-batch inference, [**ControlNet-Union-Pro 2.0**](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0), initial integration of [**PuLID**](https://github.com/ToTheBeginning/PuLID), and introduces [**Double FB Cache**](examples/flux.1-dev-double_cache.py). You can now load Nunchaku FLUX models as a single file, and our upgraded [**4-bit T5 encoder**](https://huggingface.co/nunchaku-tech/nunchaku-t5) now matches **FP8 T5** in quality!

README_ZH.md

@@ -15,6 +15,7 @@
 
 ## 最新动态
 
+- **[2025-07-31]** 🚀 **[FLUX.1-Krea-dev](https://www.krea.ai/blog/flux-krea-open-source-release) 已支持！** 欢迎参考我们的[示例脚本](./examples/flux.1-krea-dev.py)快速上手。
 - **[2025-07-13]** 🚀 官方 [**Nunchaku 文档**](https://nunchaku.tech/docs/nunchaku/) 上线！欢迎查阅详细的入门指南和资源。
 - **[2025-06-29]** 🔥 支持 **FLUX.1-Kontext**！可参考我们的[示例脚本](./examples/flux.1-kontext-dev.py)体验，在线演示见[此处](https://svdquant.mit.edu/kontext/)！
 - **[2025-06-01]** 🚀 **v0.3.0 发布！** 本次更新支持多 batch 推理、[**ControlNet-Union-Pro 2.0**](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0)、初步集成 [**PuLID**](https://github.com/ToTheBeginning/PuLID)，并引入 [**双 FB Cache**](examples/flux.1-dev-double_cache.py)。现已支持单文件加载 FLUX 模型，升级后的 [**4-bit T5 编码器**](https://huggingface.co/nunchaku-tech/nunchaku-t5) 质量媲美 **FP8 T5**！

examples/flux.1-krea-dev.py

+import torch
+from diffusers import FluxPipeline
+
+from nunchaku import NunchakuFluxTransformer2dModel
+from nunchaku.utils import get_precision
+
+precision = get_precision()  # auto-detect your precision is 'int4' or 'fp4' based on your GPU
+transformer = NunchakuFluxTransformer2dModel.from_pretrained(
+    f"nunchaku-tech/nunchaku-flux.1-krea-dev/svdq-{precision}_r32-flux.1-krea-dev.safetensors"
+)
+pipeline = FluxPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-krea-dev", torch_dtype=torch.bfloat16, transformer=transformer
+).to("cuda")
+prompt = (
+    "Tiny paper origami kingdom, a river flowing through a lush valley, bright saturated image,"
+    "a fox to the left, deer to the right, birds in the sky, bushes and tress all around"
+)
+image = pipeline(prompt, height=1024, width=1024, guidance_scale=4.5).images[0]
+image.save("flux-krea-dev.png")