Add README.

README.md

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+---
+license: apache-2.0
+tags:
+- stylegan2
+- image-generation
+---
+
+# AniCharaGAN: Anime Character Generation with StyleGAN2
+
+[![GitHub Repo stars](https://img.shields.io/github/stars/eugenesiow/practical-ml?style=social)](https://github.com/eugenesiow/practical-ml)
+
+This model uses the awesome lucidrains’s [stylegan2-pytorch](https://github.com/lucidrains/stylegan2-pytorch) library to train a model on a private anime character dataset to  generate full-body 256x256 female anime characters.
+
+Here are some samples:
+
+![Samples of anime characters and styles generated by the model](images/samples1.jpg "Samples of anime characters and styles generated by the model")
+
+## Model description
+The model generates 256x256, square, white background, full-body anime characters. It is trained using [stylegan2-pytorch](https://github.com/lucidrains/stylegan2-pytorch). It is trained to 150 epochs.
+
+## Intended uses & limitations
+You can use the model for generating anime characters and than use a super resolution library like [super_image](https://github.com/eugenesiow/super-image) to upscale.
+
+### How to use
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/eugenesiow/practical-ml/blob/master/notebooks/Anime_Character_Generation_with_StyleGAN2.ipynb "Open in Colab")
+
+Install the dependencies:
+```bash
+pip install -q stylegan2_pytorch==1.5.10
+```
+Here is how to generate images:
+```python
+import torch
+from torchvision.utils import save_image
+from stylegan2_pytorch import ModelLoader
+from pathlib import Path
+
+Path('./models/ani-chara-gan/').mkdir(parents=True, exist_ok=True)
+torch.hub.download_url_to_file('https://huggingface.co/eugenesiow/ani-chara-gan/resolve/main/model.pt',
+                               './models/ani-chara-gan/model_150.pt')
+torch.hub.download_url_to_file('https://huggingface.co/eugenesiow/ani-chara-gan/resolve/main/.config.json',
+                               './models/ani-chara-gan/.config.json')
+
+loader = ModelLoader(
+    base_dir = './', name = 'ani-chara-gan'
+)
+
+noise   = torch.randn(1, 256).cuda() # noise
+styles  = loader.noise_to_styles(noise, trunc_psi = 0.7)  # pass through mapping network
+images  = loader.styles_to_images(styles) # call the generator on intermediate style vectors
+
+save_image(images, './sample.jpg')
+```
+
+## BibTeX entry and citation info
+
+The model is part of the [practical-ml](https://github.com/eugenesiow/practical-ml) repository.
+
+[![GitHub Repo stars](https://img.shields.io/github/stars/eugenesiow/practical-ml?style=social)](https://github.com/eugenesiow/practical-ml)