LLM-Related Technology

LLM-Related Technology refers to various technologies that are connected to or used in conjunction with Large Language Models (LLMs).

• Context:
  • It can include Hardware for LLMs, such as GPUs, TPUs, and other AI Accelerators.
  • It can include Software Libraries for LLMs, such as Hugging Face Transformers, PyTorch Lightning, and DeepSpeed.
  • It can include Data Infrastructure for LLMs, such as Data Pipelines, Data Labeling Tools, and Datasets for LLM Training.
  • It can include Deployment Infrastructure for LLMs, such as Kubernetes, Docker, and Serverless Platforms.
  • It can include Testing and Evaluation Tools for LLMs, such as Language Model Evaluation Metrics and Benchmark Datasets.
  • It can include Prompt Engineering Tools, such as OpenAI Playground, Promptify, and Prompt Base.
  • ...
• Example(s):
  • NVIDIA A100 GPUs used for training LLMs.
  • Hugging Face Transformers Library used for working with LLMs in PyTorch and TensorFlow.
  • Amazon SageMaker used for deploying LLMs.
  • GLUE Benchmark used for evaluating LLM performance on various NLP tasks.
  • ...
• Counter-Example(s):
  • Convolutional Neural Networks (CNNs) which are primarily used in Computer Vision tasks.
  • Reinforcement Learning Algorithms which are used in Sequential Decision Making problems.
• See: Large Language Models, AI Infrastructure, NLP Libraries, ML Evaluation, LLM Strategy.

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