| --- |
| license: mit |
| tags: |
| - pytorch |
| - diffusers |
| - unconditional-image-generation |
| --- |
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| # English Version |
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| ## Model Card for My First pre-trained model -- test2train_anime_face |
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| This model is a diffusion model for unconditional image generation of anime style 64*64 face pic. |
| The training set uses [anime-faces](https://huggingface.co/datasets/huggan/anime-faces). This is a dataset consisting of 21551 anime faces scraped from www.getchu.com, which are then cropped using the anime face detection algorithm in https://github.com/nagadomi/lbpcascade_animeface. |
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| Generating multiple pictures at once is prone to broken face. It has been tested that one picture at a time produces the best results and is not prone to broken faces. |
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| ### Usage |
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| ```python |
| from diffusers import DDPMPipeline |
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| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
| pipeline = DDPMPipeline.from_pretrained('Chilli-b/test2train_amine_face').to(device) |
| image = pipeline().images[0] |
| image |
| ``` |
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| --- |
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| # 中文版 |
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| ## 这是我创造的第一个预训练模型—— test2train_anime_face 的模型卡。 |
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| 该模型是一个无条件扩散模型，用于生成尺寸为 64*64 的动漫风格脸部图片。 |
| 训练集使用的是[anime-faces](https://huggingface.co/datasets/huggan/anime-faces),这是一个包含从 www.getchu.com 上爬取的21551个动漫脸，然后使用 https://github.com/nagadomi/lbpcascade_animeface 中的动漫脸检测算法进行裁剪的数据集。 |
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| 一次生成多张容易出现鬼脸。实测每次出一张图的效果最好，不容易出现鬼脸。 |
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| ### 模型使用 |
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| ```python |
| from diffusers import DDPMPipeline |
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| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
| pipeline = DDPMPipeline.from_pretrained('Chilli-b/test2train_amine_face').to(device) |
| image = pipeline().images[0] |
| image |
| ``` |
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