Instructions to use virtuerdem/gan-human-faces with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use virtuerdem/gan-human-faces with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://virtuerdem/gan-human-faces") - Notebooks
- Google Colab
- Kaggle
GAN: Human Faces Generator
A Generative Adversarial Network trained to generate human faces.
Model Details
- Generator: Keras model (.keras)
- Discriminator: Keras model (.keras)
- Framework: TensorFlow/Keras
- Input dimension: 100 (latent space)
- Output: 64x64 RGB images
Usage
import tensorflow as tf
# Model yükleyin
gen = tf.keras.models.load_model('generator.keras')
# Rastgele latent vector oluşturun
import numpy as np
z = np.random.normal(0, 1, (1, 100))
# Face generate edin
fake_face = gen.predict(z)
Training Details
- Trained on: kaggle~~
- Epochs: 1000
- Batch size: 256
- Downloads last month
- 68
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