Search Results for "multiple sequence alignment"

Showing 3 open source projects for "multiple sequence alignment"

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    EasySend is a no-code platform that transforms customer journeys

    Defy form limits. 
Create digital experiences.

    Evolve forms into smart, AI-powered digital workflows that streamline your data intake and elevate customer experiences.
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  • Centralized Workload Automation and Job Scheduling Icon
    Centralized Workload Automation and Job Scheduling

    Orchestrate your entire tech stack with our no-code connectors and low-code REST API adapter

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    AIGCPanel

    AIGCPanel

    One-stop AI digital human system with video voice synthesis tools

    AIGCPanel is an open source desktop application designed as a comprehensive, all-in-one platform for creating AI-powered digital humans and media content. It integrates multiple capabilities such as video synthesis, voice synthesis, and voice cloning into a unified interface, allowing users to generate realistic audiovisual outputs with minimal setup. AIGCPanel focuses heavily on simplifying the management of local AI models by providing streamlined workflows for importing, configuring, and...
    Downloads: 22 This Week
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  • 2
    Talk to Figma MCP

    Talk to Figma MCP

    AI bridge enabling Cursor agents to read and modify Figma designs

    cursor-talk-to-figma-mcp is an open source integration that connects AI coding agents with Figma through the Model Context Protocol (MCP). It allows AI tools such as Cursor or other compatible agents to directly communicate with Figma documents and interact with design elements programmatically. Through this integration, an AI assistant can read the structure of a design, retrieve information about nodes or selections, and perform modifications to the layout or content....
    Downloads: 0 This Week
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  • 3
    dLLM

    dLLM

    dLLM: Simple Diffusion Language Modeling

    ...Unlike traditional autoregressive models that generate text sequentially token by token, diffusion language models generate text through an iterative denoising process that refines masked tokens over multiple steps. This approach allows models to reason over the entire sequence simultaneously and potentially produce more coherent outputs with bidirectional context. The project provides an integrated pipeline that standardizes how diffusion language models are trained, evaluated, and deployed, helping researchers reproduce experiments and compare results more easily. ...
    Downloads: 0 This Week
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