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--- |
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license: apache-2.0 |
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datasets: |
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- uoft-cs/cifar10 |
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- openslr/librispeech_asr |
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- udayl/UCI_HAR |
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language: |
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- en |
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metrics: |
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- bertscore |
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- accuracy |
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library_name: adapter-transformers |
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tags: |
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- code |
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- medical |
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--- |
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# UANN Model |
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## Model Description |
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This is the Universal Adaptive Neural Network (UANN) designed for multi-modal AI agents. The model incorporates a Mixture of Experts (MoE) architecture. |
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## Usage |
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```python |
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import torch |
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from models.moe_model import MoEModel |
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# Initialize model |
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model = MoEModel(input_dim=512, num_experts=3) |
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# Dummy inputs for testing |
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vision_input = torch.randn(1, 3, 32, 32) |
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audio_input = torch.randn(1, 100, 40) |
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sensor_input = torch.randn(1, 10) |
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# Forward pass |
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output = model(vision_input, audio_input, sensor_input) |
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print(output) |
