LM Studio
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Pricing model
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LM Studio is a software app enabling users to execute large language models (LLMs) on their personal devices without requiring an internet connection, thus providing improved privacy and data security. It accommodates various models like LLaMa, Falcon, MPT, Gemma, and others from Hugging Face repositories. Users can engage with models via an in-app Chat UI or a local server that is OpenAI's API compatible. LM Studio is perfect for individuals aiming to utilize LLMs for personal projects, research, or development while keeping full control of their data. This approach to locally running machine learning models is particularly appealing to those who prioritize privacy or handle sensitive information.
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Effortlessly store, categorize, and utilize your AI prompts. Whether you're a digital artist, copywriter, or an AI enthusiast, ensure your text prompts are well-organized and easy to access for chat gpt, jasper, stable diffusion, and beyond.
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PrepAI is a sophisticated ed-tech solution that streamlines the generation, management, and evaluation of mock exams in diverse subjects. It produces top-notch questions in various formats, conforms to Bloom's taxonomy, and accommodates visual content. This tool is ideal for exam organizers, teachers, learners, and HR specialists aiming to conserve time, guarantee uniformity, and elevate the educational process through precise and effective assessments.
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Drawer AI is a smart online platform designed to automate electrical takeoffs and estimating by quickly extracting and calculating devices, fixtures, and circuits from PDF electrical drawings. Instead of taking hours, it completes these tasks in minutes. The software manages device counting, branch circuit routing, wire sizing, and report creation, allowing electrical contractors and estimators to finish bids as much as 70% quicker with enhanced accuracy. Those in the electrical industry opt for Drawer AI to boost their bid production, minimize expensive mistakes, and achieve a competitive edge in the marketplace with more efficient estimating methods.