Instructions to use LibreYOLO/LibrePRX1024-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LibreYOLO/LibrePRX1024-beta with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LibreYOLO/LibrePRX1024-beta", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
LibrePRX1024-beta
PRX, Photoroom's 1.3B text-to-image transformer trained from scratch, with a T5Gemma 2B text encoder and the FLUX.1 VAE. Native resolution 1024; Photoroom's 1024 preview checkpoint. Mirrored for LibreYOLO.
from libreyolo import LibreGen
model = LibreGen("prx-1024-beta") # downloads this repo
model("a red fox sleeping in fresh snow").save("fox.png")
libreyolo generate prompt="a red fox" model=prx-1024-beta
Install libreyolo[gen].
This is a mirror, not a new model
The weights are Photoroom's. Nothing was retrained, converted or re-encoded;
every file is byte-identical to upstream and keeps upstream's diffusers
pipeline layout, so diffusers loads this folder as it is.
- Upstream repository:
Photoroom/prx-1024-t2i-beta - Upstream revision:
0370504b9a433fbdff814b8fcba9da03bf72a7a3 - Announcement: We're open-sourcing our text-to-image model and the process behind it
| File | SHA-256 |
|---|---|
text_encoder/model-00001-of-00003.safetensors |
e7a37fef2b11c87a9a2a43c26fcd7199c1d1b203ef11e10863a56611c8fdb57f |
text_encoder/model-00002-of-00003.safetensors |
49da6c85ed4ff10f7f1afaa5a37a0b292fdb58aa855916ef584d697155a9bf58 |
text_encoder/model-00003-of-00003.safetensors |
1a6361ba65805092625aa4e2b3b8d42b810ab836682ddc8277088c9a251b4084 |
text_encoder/model.safetensors |
75bed3ac53b4fcde6b72d976809d4046a97cebcd414801fb81a16cbcf5c70654 |
transformer/diffusion_pytorch_model.safetensors |
35f8987e3120ecf2ddaaab9547900f41f4c32788e49fb59287ea7cd7d13933b1 |
vae/diffusion_pytorch_model.safetensors |
8c717328c8ad41faab2ccfd52ae17332505c6833cf176aad56e7b58f2c4d4c94 |
License
The PRX weights are Apache-2.0, as published by Photoroom. The bundled T5Gemma 2B text encoder is provided under and subject to the Gemma Terms of Use, and you may not use it for the restricted uses in the Gemma Prohibited Use Policy. The FLUX.1 [schnell] VAE is Apache-2.0. See LICENSE and NOTICE.
Model tree for LibreYOLO/LibrePRX1024-beta
Base model
Photoroom/prx-1024-t2i-beta