| datasets: | |
| - merve/anime-faces | |
| library_name: tf-keras | |
| license: apache-2.0 | |
| tags: | |
| - dcgan | |
| ## Model description | |
| Anime face generator model using [TensorFlow DCGAN example](https://www.tensorflow.org/tutorials/generative/dcgan). | |
| ## Training and evaluation data | |
| Model is trained on [anime faces dataset](https://huggingface.co/datasets/merve/anime-faces). The dataset consists of 21551 anime faces scraped from www.getchu.com, which are then cropped using the anime face detection algorithm [here](https://github.com/nagadomi/lbpcascade_animeface). All images are resized to 64 * 64 for the sake of convenience. The model takes a noise as input and then Conv2DTranspose is used to do upsampling. If you want to pass this to another discriminator, the output shape consists of 28x28 images. | |
| ## How to use this model | |
| You can use this model to generate new anime faces. If you want to continuously train, use with [discriminator](https://huggingface.co/merve/anime-faces-discriminator) using `tf.GradientTape()` as mentioned in the DCGAN tutorial. | |
| ``` | |
| from huggingface_hub import from_pretrained_keras | |
| model = from_pretrained_keras("merve/anime-faces-generator") | |
| ``` | |
| You can generate examples using a noise. | |
| ``` | |
| seed = tf.random.normal([number_of_examples_to_generate, noise]) | |
| predictions = model(seed, training=False) # inference mode | |
| ``` | |
| ## Intended use and biases | |
| This model is not intended for production. | |
| ### Generated images | |
|  |