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Local III
Overview :
Developed by over 100 contributors from around the world, Local III introduces a user-friendly local model browser deeply integrated with inference engines like Ollama. It provides tailored configurations for open-source models like Llama3, Moondream, and Codestral, ensuring reliable offline code interpretation. Local III also introduces a free, hosted, optional model via the interpreter – model i. Conversations with model i will be used to train our own open-source computer control language model.
Target Users :
Local III targets developers and technical personnel who wish to access machine intelligence locally for code interpretation and execution. It empowers users who prioritize privacy and require offline access to AI models.
Use Cases
Developers utilize Local III for local code writing and testing, eliminating reliance on online services.
Data scientists leverage Local III to analyze and process data in offline environments.
Educational institutions employ Local III as a teaching tool to educate students on utilizing AI technologies in local settings.
Features
Interactive setup to select inference providers, models, and download new models.
Introduction of model i, offering a seamless experience while contributing to the training of local language models.
Deep integration with Ollama models, simplifying model setup commands.
Optimized configurations, providing recommended settings for SOTA local language models like codestral, llama3, and qwen.
Local visual support, enabling image conversion to image descriptions generated by Moondream and OCR extraction.
Experimental local operating system mode, allowing Open Interpreter to control mouse, keyboard, and view the screen.
How to Use
1. Visit the Local III official website and download the plugin.
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2. Install and launch the plugin, selecting the desired inference provider and model.
3. Utilize the interactive setup to download any required new models.
4. Configure recommended settings to optimize performance for specific models.
5. Leverage Local Explorer for local model management and utilization.
6. Enable local visual and operating system modes when needed for advanced interactive capabilities.
7. Participate in conversations and model training to contribute to the development of open-source AI.
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