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Back to kleveross/ormb

Open-source alternatives to Ormb

11 open-source projects similar to kleveross/ormb, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Ormb alternative.

  • alexsjones/llmfitAlexsJones avatar

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    ClearML is a comprehensive MLOps platform designed to manage the entire machine learning lifecycle. It functions as an experiment tracking tool, a data versioning system, and a pipeline orchestrator, while providing infrastructure for GPU cluster management and model serving. The platform is distinguished by its ability to handle hybrid-cloud compute scheduling and fractional GPU allocation, allowing multiple workloads to share a single hardware accelerator. It employs a metadata-based approach to data versioning, using virtual views to track large datasets and artifacts without duplicating r

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  • comet-ml/comet-examplescomet-ml avatar

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  • dottxt-ai/outlinesdottxt-ai avatar

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    13,446View on GitHub↗

    Outlines is a library designed to ensure machine-readable output from generative models by applying programmatic constraints during the token sampling process. It functions as a toolkit for forcing large language models to generate text that strictly adheres to JSON schemas, regular expressions, and formal grammars, enabling the integration of model responses into existing software systems. The library distinguishes itself by integrating formal language rules directly into the sampling loop. It achieves this by converting regular expressions into deterministic finite automata and utilizing lo

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  • guidance-ai/llguidanceguidance-ai avatar

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    Performance results from MaskBench

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  • iterative/dvciterative avatar

    iterative/dvc

    15,680View on GitHub↗

    DVC is a data versioning tool and pipeline orchestrator designed to track large datasets and machine learning models. It functions as a system for managing large data artifacts by storing lightweight metadata in version control while keeping the actual binaries in a separate cache. The project serves as an experiment tracker and remote storage synchronizer, enabling the execution and comparison of machine learning iterations based on hyperparameters and performance metrics. It provides a bridge for pushing and pulling these large data artifacts between local environments and cloud or on-premi

    Python
    View on GitHub↗15,680
  • iterative/mlemiterative avatar

    iterative/mlem

    718View on GitHub↗

    🐶 A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one day🤞

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  • mlflow/mlflowmlflow avatar

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    Pythonagentopsagentsai
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  • mostlygeek/llama-swapmostlygeek avatar

    mostlygeek/llama-swap

    4,786View on GitHub↗

    Llama-swap is a local inference orchestrator and API gateway for large language models. It functions as an OpenAI API proxy that manages the lifecycle of multiple local model servers, automatically starting and stopping them to swap models based on incoming request identifiers. The project distinguishes itself through dynamic model swapping and hardware optimization. It utilizes a specialized matrix-based concurrency control to define which models can run simultaneously and employs cost-based eviction to remove inactive servers from memory based on relative resource costs. The system provide

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  • vertaai/modeldbVertaAI avatar

    VertaAI/modeldb

    1,746View on GitHub↗

    Open Source ML Model Versioning, Metadata, and Experiment Management

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  • wandb/wandbwandb avatar

    wandb/wandb

    10,844View on GitHub↗

    Wandb is a centralized platform for machine learning experiment tracking, model registry management, and workflow orchestration. It provides a comprehensive suite of tools for logging, visualizing, and versioning training metrics, model artifacts, and hyperparameter sweeps to ensure reproducibility across development cycles. The platform also functions as an observability tool for large language model applications, enabling the tracing of execution steps, token usage, and reasoning processes. The project distinguishes itself through its event-driven automation capabilities, which allow users

    Pythonaicollaborationdata-science
    View on GitHub↗10,844