WannabeArchitect/TinyAgent-1.1B-MLX

Hugging Face
TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:1.1BQuant:BF16Context Size:2kPublished:Apr 2, 2025Architecture:Transformer Featherless Exclusive Warm

TinyAgent-1.1B-MLX is a 1.1 billion parameter language model developed by WannabeArchitect, converted to MLX format from squeeze-ai-lab's TinyAgent-1.1B. This model is optimized for efficient deployment and inference on Apple Silicon, leveraging the MLX framework. Its primary use case is for local, resource-constrained agentic applications and rapid prototyping on compatible hardware.

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TinyAgent-1.1B-MLX Overview

TinyAgent-1.1B-MLX is a 1.1 billion parameter language model, specifically converted by WannabeArchitect to the MLX format for optimized performance on Apple Silicon. This conversion facilitates efficient local inference and deployment, making it suitable for developers working within the Apple ecosystem. The original model, TinyAgent-1.1B, was developed by squeeze-ai-lab.

Key Capabilities

  • MLX Optimization: Engineered for high-performance inference on Apple Silicon (Macs with M-series chips).
  • Lightweight: With 1.1 billion parameters, it offers a balance between capability and computational efficiency.
  • Local Deployment: Designed for easy integration into local applications and development workflows.

Good for

  • Agentic Applications: Ideal for building and experimenting with small-scale AI agents on local hardware.
  • Rapid Prototyping: Enables quick iteration and testing of language model-powered features on Apple devices.
  • Resource-Constrained Environments: Suitable for scenarios where larger models are impractical due to hardware limitations.

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