Use the comparison tool below to compare the top AI Tools for LM Studio on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
-
1
Linkly AI
Linkly AI
$29 per yearLinkly AI is an innovative knowledge engine designed with an AI agent-first approach that transforms your existing computer files into a dynamic, searchable context layer for AI assistants. This tool efficiently analyzes and catalogs a variety of materials, including notes, educational resources, bookmarks, knowledge repositories, audio recordings, meeting videos, images, e-books, and more, enabling agents to search through, compare, and access this information without requiring users to manually create a knowledge base. It supports a wide range of formats such as PDF, Markdown, JPG, PNG, MOV, MP4, PPTX, TXT, WAV, DOCX, HTML, MP3, and EPUB, ensuring versatility in handling different types of content. Each document is equipped with a structured index that gradually reveals pertinent sections, allowing agents to navigate extensive files with intention rather than indiscriminately opening everything. The system incorporates cross-language semantic search capabilities utilizing a local multilingual model, enabling effective searches across numerous languages, with results delivered in under half a second. Additionally, data remains on your device by default, and any third-party tools or models access only the essential snippets required, safeguarding the integrity of your original files. By streamlining the way information is processed and accessed, Linkly AI significantly enhances productivity and knowledge retrieval. -
2
StarCoder
BigCode
FreeStarCoder and StarCoderBase represent advanced Large Language Models specifically designed for code, developed using openly licensed data from GitHub, which encompasses over 80 programming languages, Git commits, GitHub issues, and Jupyter notebooks. In a manner akin to LLaMA, we constructed a model with approximately 15 billion parameters trained on a staggering 1 trillion tokens. Furthermore, we tailored the StarCoderBase model with 35 billion Python tokens, leading to the creation of what we now refer to as StarCoder. Our evaluations indicated that StarCoderBase surpasses other existing open Code LLMs when tested against popular programming benchmarks and performs on par with or even exceeds proprietary models like code-cushman-001 from OpenAI, the original Codex model that fueled early iterations of GitHub Copilot. With an impressive context length exceeding 8,000 tokens, the StarCoder models possess the capability to handle more information than any other open LLM, thus paving the way for a variety of innovative applications. This versatility is highlighted by our ability to prompt the StarCoder models through a sequence of dialogues, effectively transforming them into dynamic technical assistants that can provide support in diverse programming tasks.
- Previous
- You're on page 1
- Next
