ai-optimization

Dive into advanced quantization techniques. Learn to implement and customize linear quantization functions, measure quantization error, and compress model weights using PyTorch for efficient and accessible AI models.

machine-learning quantization model-compression linear-quantization quantization-error ai-optimization advanced-quantization symmetric-quantization asymmetric-quantization per-tensor-granularity per-channel-granularity per-group-granularity pytorch-quantizer weight-packing 8-bit-compression 2-bit-weights

UpdatedMay 22, 2024
Jupyter Notebook

TheSPEEDO /Google-Optimizer

Star2

Optimize Google Chrome with installation tweaks, registry adjustments, flags, debloating, file compression, and AI optimizations. Reduce memory and CPU usage for faster performance and improved search results.

chrome google optimization registry-optimizer batch-file chrome-extensions cpu-usage file-compression registry-tweaks speed-boost ai-optimization performance-tweaks privacy-enhancement debloat-chrome chrome-optimization

UpdatedMar 21, 2025
Batchfile

underflow101 /ai-zipper

Star1

ai-zipper offers numerous AI model compression methods, also it is easy to embed into your own source code

model-compression model-optimizer model-optimization ai-optimization

UpdatedFeb 8, 2021
Python

ashleysally00 /agent_eval_testing_workflow

Star0

Agentic Workflow Evaluation: Text Summarization Agent. This project includes an AI agent evaluation workflow using a text summarization model with OpenAI API and Transformers library. It follows an iterative approach: generate summaries, analyze metrics, adjust parameters, and retest to refine AI agents for accuracy, readability, and performance.

machine-learning text-summarization semantic-similarity model-performance transformers-library openai-api ai-optimization ai-testing llm-evaluation ai-workflow agentic-ai ai-agent-evaluation ai-metrics readability-n

UpdatedFeb 23, 2025
Python

ksm26 /Reasoning-with-o1

Star0

This repository explores OpenAI’s o1 model, a cutting-edge AI designed for abstract reasoning, coding, and vision-based tasks. It provides insights into o1’s strengths, advanced prompting techniques, task delegation, and real-world applications, enabling developers to build intelligent, high-performance AI-driven solutions.

machine-learning deep-learning openai task-automation ai-optimization future-ai vision-ai llm prompt-engineering ai-reasoning meta-prompting ai-innovation o1model stem-ai coding-with-ai