Pre-Trained General-Purpose Neural Model

A Pre-Trained General-Purpose Neural Model is a pre-trained neural model that is a general-purpose neural model.

• Context:
  • It can (typically) support multiple tasks across various domains without task-specific training.
  • It can range from being a Base Pre-Trained General-Purpose Neural Model to being a Fine-Tuned Pre-Trained General-Purpose Neural Model.
  • It can range from being a Pre-Trained General-Purpose Neural Encoder-only Model to being a ____ Model to being a ____ Model.
  • It can range from being a Single Datatype Pre-Trained General-Purpose Neural Model to being a multimodal neural model.
  • ...
• Example(s):
  • Base Encoder-Only Text Model], such as:
    • BERT, RoBERTa, ALBERT, DistilBERT.
    • ...
  • Pre-Trained General-Purpose LLMs, such as:
    • Foundational Base LLM, such as GPT-3
    • Foundational Instruct LLM, such as LLaMA-Instruct model.
    • ...
  • Foundational Computer Vision Models, such as:
    • Foundational Basic CV Model, such as: ResNet, a convolutional neural network model for image recognition.
    • Foundational Object Detection Model, such as: YOLO, a real-time object detection system.
  • ...
• Counter-Example(s):
  • Task-Specific Neural Models, which are designed for specific tasks without the versatility of general-purpose models.
• See: Large Language Models, Multimodal Models, Computer Vision Models

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