Neural Network: Difference between revisions

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A Neural Network in the {{software}} is a pre-trained network that can be used by an [[Inference Overlay]] to classify or detect patterns and features given one or more input [[Overlay]]s.
The {{software}} currently support three types of neural networks running on Tygron [[GPU Cluster]]s:
Neural Networks are stored in the {{software}} as data [[item]]s with a reference to an [[ONNX]]-file (Open Neural Network Exchange format<ref name="ONNX"/>). Multiple type of neural networks<ref name="Cheatsheet"/> are supported.


Input and output for neural networks is handled using data tensors. These tensors are multi-dimensional data arrays. They are automatically identified when selecting or adding a new Neural Network.
* RCNN: [[Region-based Convolutional Neural Network (Inference Overlay)|Region-based Convolutional Neural Network]] used in the [[Inference Overlay|AI Inference Overlay]].


* LLM: [[Large Language Model (LLM)|Large Language Model ]] used in the [[Chat Channel]]s.


Whether a Neural Network classifies or detects objects given an input depends on its inference model. Such a model consists using AI-software, such as [[PyTorch]].
* EMBEDDING: Embedding model used for AI assisted data search.
 
{{article end
|seealso=
* [[Inference Overlay]]
* [[ONNX]]
* [[PyTorch]]
}}
 
==References==
<references>
<ref name="ONNX">ONNX ∙ found at: https://onnx.ai/ (last visited: 2024-09-21)</ref>
<ref name="Cheatsheet">Cheatsheet ∙ found at: https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-convolutional-neural-networks</ref>
</references>

Latest revision as of 15:51, 2 July 2026

The Tygron Platform currently support three types of neural networks running on Tygron GPU Clusters:

  • EMBEDDING: Embedding model used for AI assisted data search.
Retrieved from "https://support.tygron.com/w/index.php?title=Neural_Network&oldid=88194"