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--- |
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license: wtfpl |
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language: |
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- en |
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metrics: |
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- accuracy |
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- f1 |
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base_model: Wonder-Griffin/TraXL |
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pipeline_tag: text-generation |
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library_name: transformers |
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tags: |
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- text-generation-inference |
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- question-answering |
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- casual-language-modeling |
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- conversational |
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- hybrid-model |
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- CNN |
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- RNN |
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--- |
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##Model Card for ZEUS## |
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##License: Do What The F\*ck You Want To Public License## |
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##Model Description: |
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ZEUS is a novel AI model designed to handle a wide range of problems. It is a hybrid model that combines the strengths of various architectures, including transformer-based models, convolutional neural networks, and recursive neural networks. ZEUS is capable of processing multiple input modalities, including text, images, and audio. |
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##Developed by: Morgan Griffin, WongrifferousAI and Wonder-Griffin |
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##Shared by: WongrifferousAI and Wonder-Griffin |
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##Model type: Hybrid model (transformer-based, CNN, RNN) |
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##Language(s) (NLP): English (primary), multilingual support planned |
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##License: Do What The F\*ck You Want To Public License |
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##Repository: https://github.com/wongrifferousAI/ZEUS |
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##Uses: |
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##Direct Use: |
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ZEUS can be used as a general-purpose AI model for a wide range of applications, including but not limited to: |
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*Natural Language Processing (NLP) |
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*Computer Vision |
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*Speech Recognition |
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*Multimodal Learning |
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##Downstream Use: |
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ZEUS can be fine-tuned for specific tasks, such as: |
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*Sentiment Analysis |
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*Image Classification |
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*Speech-to-Text |
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*Multimodal Fusion |
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##Out-of-Scope Use: |
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ZEUS is not intended for use in applications that require: |
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*Real-time processing (due to its complex architecture) |
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*Extremely large input sizes (due to memory constraints) |
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*Bias, Risks, and Limitations: |
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ZEUS may exhibit biases present in its training data, particularly in NLP tasks. |
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The model's performance may degrade when faced with out-of-distribution inputs or tasks. |
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ZEUS requires significant computational resources and memory, which may limit its deployment in certain environments. |
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##Recommendations: |
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Users should carefully evaluate ZEUS's performance on their specific task and dataset before deployment. |
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Users should be aware of the potential biases and limitations of the model and take steps to mitigate them. |
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How to Get Started with the Model: |
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##Clone the ZEUS repository: git clone https://github.com/wongrifferousAI/ZEUS.git |
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Install the required dependencies: pip install -r requirements.txt |
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Load the pre-trained model: model = ZeusModel(vocab_size=50000, embed_dim=512, image_dim=256, audio_dim=128, num_heads=12, reflection_dim=512, num_experts=4) |
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Fine-tune the model on your specific task and dataset. |
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##Training Details: |
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##Training Hyperparameters: |
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*Batch size: 32 |
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*Number of epochs: 10 |
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*Learning rate: 1e-4 |
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*Optimizer: Adam |
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*Training Regime: [Not Applicable] |
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##Model Architecture: Hybrid model (transformer-based, CNN, RNN)## |
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##For more information, please visit the ZEUS repository: https://github.com/wongrifferousAI/ZEUS## |
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##Model Card Authors: |
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***Morgan Griffin, WongrifferousAI and Wonder-Griffin*** |
