#swift #mlx

These examples help you use machine learning in Swift programming. You can train models, generate text and images, and analyze pictures using pre-made tools. For instance, you can download and train a model to recognize handwritten numbers or generate images from text prompts. These tools run on iOS, macOS, and other platforms, making it easy to integrate machine learning into your projects. By using these examples, you can quickly start working with advanced AI features without starting from scratch, saving you time and effort.

https://github.com/ml-explore/mlx-swift-examples

#cplusplus #mlx

MLX is a powerful tool for machine learning on Apple devices. It has a familiar interface similar to NumPy, making it easy to use. MLX supports many programming languages like Python, C++, and Swift. It allows computations to be done lazily, which means they only happen when needed, saving resources. MLX also works on both CPUs and GPUs without needing to move data around, thanks to its unified memory model. This makes it efficient for training and deploying models, helping users explore new ideas quickly.

https://github.com/ml-explore/mlx

#typescript #electron #llama #llms #lora #mlx #rlhf #transformers

Transformer Lab is a free, open-source tool that lets you easily work with large language models on your own computer, offering one-click downloads for popular models like Llama3 and Mistral, fine-tuning across different hardware (including Apple Silicon and GPUs), and features like chatting, training, and evaluating models through a simple interface—saving you from complex setups like CUDA or Python version issues[1][2][5].

https://github.com/transformerlab/transformerlab-app

#python #apple_silicon #audio_processing #mlx #multimodal #speech_recognition #speech_synthesis #speech_to_text #text_to_speech #transformers

MLX-Audio is a powerful tool for converting text into speech and speech into new audio. It works well on Apple Silicon devices, like M-series chips, making it fast and efficient. You can choose from different languages and voices, and even adjust how fast the speech is. It also includes a web interface where you can see audio in 3D and play your own files. This tool is helpful for making audiobooks, interactive media, and personal projects because it's easy to use and provides high-quality audio quickly.

https://github.com/Blaizzy/mlx-audio

#python #llms #mlx

MLX LM is a Python tool that helps you run and fine-tune large language models (LLMs) efficiently on Apple Silicon Macs. It connects easily to thousands of models on Hugging Face, supports model quantization to save memory, and allows distributed training. You can generate text or chat with models via simple commands or Python code. It also offers features like prompt caching and memory optimization for handling long texts, making it faster and less resource-heavy. This means you can run powerful AI models locally on your Mac without needing expensive cloud services, saving cost and improving speed.

https://github.com/ml-explore/mlx-lm