Zeus / README.md
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metadata
license: wtfpl
language:
  - en
metrics:
  - accuracy
  - f1
base_model: Wonder-Griffin/TraXL
pipeline_tag: text-generation
library_name: transformers
tags:
  - text-generation-inference
  - question-answering
  - casual-language-modeling
  - conversational
  - hybrid-model
  - CNN
  - RNN

##Model Card for ZEUS##

##License: Do What The F*ck You Want To Public License##

##Model Description:

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.

##Developed by: Morgan Griffin, WongrifferousAI and Wonder-Griffin

##Shared by: WongrifferousAI and Wonder-Griffin

##Model type: Hybrid model (transformer-based, CNN, RNN)

##Language(s) (NLP): English (primary), multilingual support planned

##License: Do What The F*ck You Want To Public License

##Repository: https://github.com/wongrifferousAI/ZEUS

##Uses:

##Direct Use:

ZEUS can be used as a general-purpose AI model for a wide range of applications, including but not limited to: *Natural Language Processing (NLP) *Computer Vision *Speech Recognition *Multimodal Learning ##Downstream Use:

ZEUS can be fine-tuned for specific tasks, such as: *Sentiment Analysis *Image Classification *Speech-to-Text *Multimodal Fusion ##Out-of-Scope Use:

ZEUS is not intended for use in applications that require: *Real-time processing (due to its complex architecture) *Extremely large input sizes (due to memory constraints) *Bias, Risks, and Limitations:

ZEUS may exhibit biases present in its training data, particularly in NLP tasks. The model's performance may degrade when faced with out-of-distribution inputs or tasks. ZEUS requires significant computational resources and memory, which may limit its deployment in certain environments. ##Recommendations:

Users should carefully evaluate ZEUS's performance on their specific task and dataset before deployment. Users should be aware of the potential biases and limitations of the model and take steps to mitigate them. How to Get Started with the Model:

##Clone the ZEUS repository: git clone https://github.com/wongrifferousAI/ZEUS.git Install the required dependencies: pip install -r requirements.txt 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) Fine-tune the model on your specific task and dataset. ##Training Details:

##Training Hyperparameters: *Batch size: 32 *Number of epochs: 10 *Learning rate: 1e-4 *Optimizer: Adam *Training Regime: [Not Applicable]

##Model Architecture: Hybrid model (transformer-based, CNN, RNN)##

##For more information, please visit the ZEUS repository: https://github.com/wongrifferousAI/ZEUS## ##Model Card Authors:

Morgan Griffin, WongrifferousAI and Wonder-Griffin