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README.md

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+---
+license: other
+license_name: krea-2-community
+license_link: https://www.krea.ai/krea-2-licensing
+pipeline_tag: text-to-image
+library_name: diffusers
+tags:
+  - text-to-image
+  - image-generation
+  - diffusion
+  - flow-matching
+  - dit
+  - krea
+base_model: krea/Krea-2-Raw
+base_model_relation: finetune
+---
+
+# Krea 2 (K2) Base - Diffusers
+
+Diffusers-format conversion of the Krea 2 **Base** checkpoint, the undistilled foundation
+model of the Krea 2 family from [Krea](https://krea.ai). The Base checkpoint carries no step
+or guidance distillation, which keeps it diverse and highly malleable. It is the checkpoint
+intended for fine-tuning, post-training, and LoRA training.
+
+LoRAs trained on Base apply cleanly to Krea 2 Turbo, so the recommended workflow is to train
+on Base and run inference on [Krea-2-Turbo-Diffusers](https://huggingface.co/CalamitousFelicitousness/Krea-2-Turbo-Diffusers).
+
+## Model Summary
+
+Krea 2 is a latent-diffusion image model trained from scratch with an emphasis on aesthetics
+and stylistic control. The architecture is a single-stream multimodal diffusion transformer.
+
+- **Transformer**: single-stream DiT, 12.9B parameters, 28 blocks at width 6144. Grouped-query
+  attention, a learned output gate, per-head QK normalization, and a 3-axis rotary embedding.
+  A text-fusion stage inside the transformer collapses twelve text-encoder hidden-state layers
+  into one conditioning stream.
+- **Text encoder**: [Qwen/Qwen3-VL-4B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct),
+  tapped at twelve intermediate layers (text-only conditioning).
+- **VAE**: the Qwen-Image autoencoder (`AutoencoderKLQwenImage`, f8, 16 latent channels).
+- **Sampler**: flow matching with a resolution-aware timestep shift.
+
+Weights are stored in their original mixed precision (bf16 matmuls, fp32 norms and modulations).
+
+## Recommended Settings
+
+Base is undistilled and uses classifier-free guidance with a negative prompt.
+
+| Setting | Value |
+| ------- | ----- |
+| Steps | 52 |
+| Guidance (CFG) | 3.5 |
+| Resolution | up to 1024 x 1024 |
+
+The timestep shift is resolution-aware: the conditioning interpolates the shift between low and
+high resolution, so no manual tuning is required across sizes.
+
+## Prompting
+
+Natural-language prompts are recommended. Long, detailed descriptions yield the best results,
+though strong images are produced from short prompts as well. For text rendering, the words to
+be rendered are wrapped in quotes. An optional prompt-expansion system prompt is available in
+the upstream [krea-2-oss](https://github.com/krea-ai) repository.
+
+## License
+
+The weights are released under the [Krea 2 community license](https://www.krea.ai/krea-2-licensing).
+
+## Citation
+
+```bibtex
+@misc{krea2,
+  title  = {Krea 2},
+  author = {Krea},
+  year   = {2026},
+  url    = {https://www.krea.ai/krea-2}
+}
+```