updated readme to feature tf support
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README.md
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README.md
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@ -26,15 +26,22 @@ pip install git+https://gitea.fabelous.app/Machine-Learning/aiuNN.git
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Here's a basic example of how to use `aiuNN` for image upscaling:
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Here's a basic example of how to use `aiuNN` for image upscaling:
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```python src/main.py
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```python src/main.py
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from aiia import AIIABase
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from aiia import AIIABase, AIIAConfig
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from aiunn import aiuNN, aiuNNTrainer
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from aiunn import aiuNN, aiuNNTrainer
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import pandas as pd
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import pandas as pd
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from torchvision import transforms
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from torchvision import transforms
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# Create a configuration and build a base model.
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config = AIIAConfig()
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ai_config = aiuNNConfig()
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base_model = AIIABase(config)
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upscaler = aiuNN(config=ai_config)
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# Load your base model and upscaler
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# Load your base model and upscaler
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pretrained_model_path = "path/to/aiia/model"
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pretrained_model_path = "path/to/aiia/model"
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base_model = AIIABase.load(pretrained_model_path, precision="bf16")
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base_model = AIIABase.from_pretrained(pretrained_model_path)
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upscaler = aiuNN(base_model)
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upscaler.load_base_model(base_model)
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# Create trainer with your dataset class
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# Create trainer with your dataset class
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trainer = aiuNNTrainer(upscaler, dataset_class=UpscaleDataset)
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trainer = aiuNNTrainer(upscaler, dataset_class=UpscaleDataset)
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