MLX Guru-AI-powered MLX framework assistant

Example

Providing step-by-step guidance on implementing a multi-layer perceptron (MLP) for the MNIST dataset, including network architecture setup, data loading, and training loop construction.

Scenario

A user aiming to develop a custom neural network model for image classification tasks can utilize MLX Guru for insights on architecture design, leveraging MLX's optimized operations for M2 GPUs.

Example

Offering strategies to debug common issues encountered during model training, such as exploding/vanishing gradients, and tips for optimizing models to leverage the computational strengths of M2 GPUs.

Scenario

Researchers trying to fine-tune large transformer models for natural language processing tasks can benefit from MLX Guru's advice on efficient memory management and computational optimization.

Example

Providing comprehensive examples and tutorials, such as fine-tuning with LoRA or QLoRA for specific tasks, complete with code snippets and performance analysis.

Scenario

Data scientists interested in exploring advanced techniques like low rank adaptation for model fine-tuning can access detailed guides and examples, facilitating practical implementation and experimentation.