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Model description

This Stable-Diffusion Model has been fine-tuned on images of the Star Trek Voyager Spaceship.

Here are some examples that were created using the model using these settings:

Prompt: photo of voyager spaceship in space, high quality, blender, 3d, trending on artstation, 8k

Negative Prompt: bad, ugly, malformed, deformed, out of frame, blurry

Denoising Steps: 50

Sample Image of the Voyager Sample Image of the Voyager Sample Image of the Voyager Sample Image of the Voyager Sample Image of the Voyager Sample Image of the Voyager

Intended uses & limitations

Anyone may use this model for non-commercial usecases under the Linked License, as long as Paragraph 5 of the Open RAIL-M License are respected as well. The original Model adheres under Open RAIL-M.

It was made solely as an experiment for keras_cv Dreambooth Training.

Since a lot of orthographic views were used, the model seems to be biased around them, and has issues creating more variance and poses. While inferring, the background appears noisy.

Training and evaluation data

Images from Rob Bonchune from Trekcore were used for training.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Hyperparameters Value
inner_optimizer.class_name Custom>RMSprop
inner_optimizer.config.name RMSprop
inner_optimizer.config.weight_decay None
inner_optimizer.config.clipnorm None
inner_optimizer.config.global_clipnorm None
inner_optimizer.config.clipvalue None
inner_optimizer.config.use_ema False
inner_optimizer.config.ema_momentum 0.99
inner_optimizer.config.ema_overwrite_frequency 100
inner_optimizer.config.jit_compile True
inner_optimizer.config.is_legacy_optimizer False
inner_optimizer.config.learning_rate 0.0010000000474974513
inner_optimizer.config.rho 0.9
inner_optimizer.config.momentum 0.0
inner_optimizer.config.epsilon 1e-07
inner_optimizer.config.centered False
dynamic True
initial_scale 32768.0
dynamic_growth_steps 2000
training_precision mixed_float16
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