GenerativeAIExamples VS mlx-examples

Compare GenerativeAIExamples vs mlx-examples and see what are their differences.

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GenerativeAIExamples mlx-examples
1 31
1,597 5,038
18.5% 7.8%
7.5 9.7
11 days ago 14 days ago
Python Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

GenerativeAIExamples

Posts with mentions or reviews of GenerativeAIExamples. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-18.

mlx-examples

Posts with mentions or reviews of mlx-examples. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-29.

What are some alternatives?

When comparing GenerativeAIExamples and mlx-examples you can also consider the following projects:

Pearl - A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.

llama-cpp-python - Python bindings for llama.cpp

PowerInfer - High-speed Large Language Model Serving on PCs with Consumer-grade GPUs

cog-whisper-diarization - Cog implementation of transcribing + diarization pipeline with Whisper & Pyannote

LLMCompiler - [ICML 2024] LLMCompiler: An LLM Compiler for Parallel Function Calling

FLaNK-OpenAi - Chat

java-iceberg-toolkit - Java implementation for performing operations on Apache Iceberg and Hive tables

MemGPT - Create LLM agents with long-term memory and custom tools 📚🦙

furnace - a multi-system chiptune tracker compatible with DefleMask modules

FLaNK-ContinuousSQL

mlx - MLX: An array framework for Apple silicon

canopy - Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone