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Update docs/source/en/api/pipelines/photon.md

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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
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David Bertoin
2025-10-16 10:50:47 +02:00
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# See the License for the specific language governing permissions and
# limitations under the License. -->
# PhotonPipeline
# Photon
Photon generates high-quality images from text using a simplified MMDIT architecture where text tokens don't update through transformer blocks. It employs flow matching with discrete scheduling for efficient sampling and uses Google's T5Gemma-2B-2B-UL2 model for multi-language text encoding. The ~1.3B parameter transformer delivers fast inference without sacrificing quality. You can choose between Flux VAE (8x compression, 16 latent channels) for balanced quality and speed or DC-AE (32x compression, 32 latent channels) for latent compression and faster processing.