Showing 4 open source projects for "idle"

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  • 1
    td

    td

    Telegram client, in Go. (MTProto API)

    Telegram MTProto API client in Go for users and bots.
    Downloads: 8 This Week
    Last Update:
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  • 2
    herdr

    herdr

    Agent multiplexer that lives in your terminal

    ...Users can organize agent sessions into workspaces, tabs, and split panes while keeping visibility into what each agent is doing. The sidebar shows whether agents are blocked, working, done, or idle, so large multi-agent workflows are easier to supervise. Sessions continue running after detach, which allows users to reconnect later from another terminal or over SSH. The project is distributed as a lightweight Rust binary for Linux, macOS, and beta Windows support. It also includes a local socket API and CLI so agents can create panes, read output, and orchestrate terminal workflows themselves.
    Downloads: 7 This Week
    Last Update:
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  • 3
    Profile Data

    Profile Data

    Analyze computation-communication overlap in V3/R1

    ...The repository contains JSON trace files like train.json, prefill.json, decode.json, and associated assets. Users can load them into tools like Chrome tracing to inspect GPU idle times, overlapping operations, and scheduling alignment. The idea is to bring transparency to internal efficiency tradeoffs, enabling researchers to reproduce, analyze, or improve on DeepSeek’s parallelism strategies. The README explains how trace data corresponds to forward/backward chunks, settings (e.g. EP64, TP1, 4K sequence length), and notes that pipeline communication is excluded for simplicity.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Machine-Learning-Flappy-Bird

    Machine-Learning-Flappy-Bird

    Machine Learning for Flappy Bird using Neural Network

    ...The system simulates a population of birds that each possess their own neural network, which acts as a decision-making controller during gameplay. The neural network receives input features representing the bird’s position relative to the next obstacle and determines whether the bird should flap or remain idle. Over successive generations, a genetic algorithm evolves the neural networks by selecting high-performing agents and recombining their parameters to produce improved offspring. This process allows the AI agents to gradually learn better strategies for navigating the obstacles and surviving longer in the game environment.
    Downloads: 0 This Week
    Last Update:
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