Local AI
Overview of Local AI
Local AI: Your Private AI Playground
What is Local AI? Local AI is a free and open-source native application designed to simplify the process of experimenting with AI models locally. It allows users to run AI inferences offline and in private, without requiring a GPU.
Key Features of Local AI:
- CPU Inferencing: Adapts to available threads and supports GGML quantization (q4, 5.1, 8, f16).
- Model Management: Centralized location to keep track of AI models, with resumable downloads and usage-based sorting.
- Digest Verification: Ensures the integrity of downloaded models with BLAKE3 and SHA256 digest compute features.
- Inferencing Server: Start a local streaming server for AI inferencing in just a few clicks.
How does Local AI work?
Local AI leverages a Rust backend for memory efficiency and a compact footprint (under 10MB on Mac M2, Windows, and Linux .deb). The application provides a user-friendly interface for:
- Downloading and managing AI models from various sources.
- Verifying the integrity of downloaded models using cryptographic digests.
- Running inference sessions on the CPU without requiring a GPU.
- Starting a local streaming server for AI inferencing.
How to use Local AI?
Using Local AI is designed to be straightforward:
- Download: Download and install the application for your operating system (.MSI, .EXE, M1/M2, Intel, AppImage, .deb).
- Model Management: Select a directory to store your AI models. Local AI will track and manage the models in that location.
- Inference: Load a model and start an inference session with just a few clicks. You can use the built-in quick inference UI or start a streaming server for more advanced applications.
- Digest Verification: Verify the integrity of your downloaded models using the BLAKE3 and SHA256 digest compute feature.
Who is Local AI for?
Local AI is ideal for:
- AI Enthusiasts: Individuals interested in experimenting with AI models without the need for expensive hardware or complex setups.
- Privacy-Conscious Users: Those who want to run AI inferences offline and in private, without sending data to external servers.
- Developers: Who need a simple and efficient way to test and deploy AI models locally.
Why choose Local AI?
- Ease of Use: Simplifies the process of experimenting with AI models.
- Privacy: Runs AI inferences offline and in private.
- Efficiency: Uses a Rust backend for memory efficiency and a compact footprint.
- Versatility: Supports a variety of AI models and applications.
Upcoming Features
The Local AI team is actively working on new features, including:
- GPU Inferencing
- Parallel sessions
- Nested directory for model management
- Custom sorting and searching
- Model explorer and search
- Audio/image inferencing server endpoints
In conclusion, Local AI is a valuable tool for anyone looking to experiment with AI models locally, offering a user-friendly interface, robust features, and a commitment to privacy and efficiency. What is the best way to start experimenting with AI models? With Local AI, it's easier than ever. Try it out today!
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