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NOTICE

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+Photoroom PRX
+Copyright 2025 Photoroom Inc..
+
+This release includes the model weights of Google's T5 Gemma 2B-2B text encoder available at https://huggingface.co/google/t5gemma-2b-2b-ul2, as well as the model weights of the Flux VAE part of the Flux.1 [schnell] model available at https://huggingface.co/black-forest-labs/FLUX.1-schnell.
+
+Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms.
+Flux.1 [schnell] is licensed under the Apache License 2.0.

README.md

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+---
+pipeline_tag: text-to-image
+library_name: diffusers
+license: apache-2.0
+tags:
+- diffusion
+- text-to-image
+- photoroom
+- prx
+- open-source
+- image-generation
+- flow-matching
+demo: https://huggingface.co/spaces/Photoroom/PRX-1024-beta-version
+model_type: diffusion-transformer
+inference: true
+---
+
+# PRX: Open Text-to-Image Generative Model
+
+![PRX](https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/ZiHS6kQv64EArhBcv7_Yk.jpeg)
+
+**PRX (Photoroom Experimental)** is a **1.3-billion-parameter text-to-image model trained entirely from scratch** and released under an **Apache 2.0 license**.
+
+It is part of Photoroom’s broader effort to **open-source the complete process** behind training large-scale text-to-image models — covering architecture design, optimization strategies, and post-training alignment. The goal is to make PRX both a **strong open baseline** and a **transparent research reference** for those developing or studying diffusion-transformer models.
+
+For more information, please read our [announcement blog post](https://huggingface.co/blog/Photoroom/prx-open-source-t2i-model).
+
+## Model description
+
+PRX is designed to be **lightweight yet capable**, easy to fine-tune or extend, and fully open.
+
+PRX generates high-quality images from text using a simplified MMDiT architecture where text tokens don’t update through transformer blocks. It uses flow matching with discrete scheduling for efficient sampling and Google’s T5-Gemma-2B-2B-UL2 model for multilingual text encoding. The model has around **1.3B parameters** and delivers fast inference without sacrificing quality. You can choose between **Flux VAE** for balanced quality and speed, or **DC-AE** for higher latent compression and faster processing.
+
+This card in particular describes `Photoroom/prx-256-t2i-sft`, one of the PRX model variants:
+
+- **Resolution:** 256 pixels
+- **Architecture:** PRX (MMDiT-like diffusion transformer variant)  
+- **Latent backbone:** Flux's VAE
+- **Text encoder:** T5-Gemma-2B-2B-UL2
+- **Training stage:** Supervised fine-tuning (SFT)
+- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
+
+For other checkpoints, browse the full [PRX collection](https://huggingface.co/collections/Photoroom/prx).
+
+## Example usage
+
+You can use PRX directly in [Diffusers](https://huggingface.co/docs/diffusers/main/en/api/pipelines/prx):
+
+```python
+from diffusers.pipelines.prx import PRXPipeline
+
+pipe = PRXPipeline.from_pretrained(
+    "Photoroom/prx-256-t2i-sft",
+    torch_dtype=torch.bfloat16
+).to("cuda")
+
+prompt = "A front-facing portrait of a lion in the golden savanna at sunset"
+image = pipe(prompt, num_inference_steps=28, guidance_scale=5.0).images[0]
+image.save("lion.png")
+```
+
+## Visual examples and demo
+
+Here are some examples from one of our best checkpoints so far ([Photoroom/prx-1024-t2i-beta](https://huggingface.co/Photoroom/prx-1024-t2i-beta)).
+
+<div style="display:flex; justify-content:center; width:100%;">
+  <table style="border-collapse:collapse; width:100%; max-width:900px; table-layout:fixed;">
+    <tr>
+      <td><img src="https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/ljWO7dK-_CKypruXcApeN.webp" style="width:100%; height:auto;"/></td>
+      <td><img src="https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/IDHiXpRlUISeJxXtJM6fW.webp" style="width:100%; height:auto;"/></td>
+      <td><img src="https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/HemYHcMexWnAuYYor5Ztx.webp" style="width:100%; height:auto;"/></td>
+    </tr>
+    <tr>
+      <td><img src="https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/kEUd7dO_30ngn__scTH3M.webp" style="width:100%; height:auto;"/></td>
+      <td><img src="https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/jGkseXch9HWfB48Z-k5OX.webp" style="width:100%; height:auto;"/></td>
+      <td><img src="https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/5YnGFBiM1IHrzLh2h7q7t.webp" style="width:100%; height:auto;"/></td>
+    </tr>
+    <tr>
+      <td><img src="https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/OrMntTSvpE8GH1YrBNgZD.webp" style="width:100%; height:auto;"/></td>
+      <td><img src="https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/Aglz2CljITrEY4V-Q-P60.webp" style="width:100%; height:auto;"/></td>
+      <td><img src="https://cdn-uploads.huggingface.co/production/uploads/68d136d7307413e80188d819/h47OBkGOsKVmq51KSRaRu.webp" style="width:100%; height:auto;"/></td>
+    </tr>
+  </table>
+</div>
+
+[PRX Demo on Hugging Face Spaces](https://huggingface.co/spaces/Photoroom/PRX-1024-beta-version) — interactive text-to-image demo for `Photoroom/prx-1024-t2i-beta`.
+
+## Training details
+
+PRX models were trained from scratch using recent advances in diffusion and flow-matching training. We experimented with a range of modern techniques for efficiency, stability, and alignment, which we’ll cover in more detail in our upcoming series of research posts:
+
+- [Part 0: Overview and release](https://huggingface.co/blog/Photoroom/prx-open-source-t2i-model)
+- Part 1: Design experiments and architecture benchmark *(coming soon)*
+- Part 2: Accelerating training *(coming soon)*
+- Part 3: Post-pretraining *(coming soon)*
+
+## Other PRX models
+
+You can find additional checkpoints in the [PRX collection](https://huggingface.co/collections/Photoroom/prx):
+- **Base** – pretrained model before alignment; best starting point for fine-tuning or research
+- **SFT** — supervised fine-tuned model; produces more aesthetically pleasing, ready-to-use generations
+- **Latent backbones** — Flux's and DC-AE VAEs
+- **Distilled** – 8-step generation with LADD
+- **Resolutions** – 256, 512, and 1024 pixels
+
+## License
+
+PRX is available under an **Apache 2.0 license**.
+
+## Use restrictions
+
+You must not use PRX models for:
+
+1. any of the restricted uses set forth in the [Gemma Prohibited Use Policy](ai.google.dev/gemma/prohibited_use_policy);
+2. or any activity that violates applicable laws or regulations.