Weights & Biases Alternatives

Tracks and optimizes machine learning experiments, models, and collaborations, streamlining development and reproducibility across the entire ML workflow.
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MLflow

If you're looking for a Weights & Biases alternative, MLflow is a good choice. It's an open-source MLOps platform that helps you develop and deploy machine learning and generative AI projects. MLflow offers experiment tracking, logging and model management, and is a good all-purpose tool for managing the ML project lifecycle. It works with popular deep learning frameworks like PyTorch, TensorFlow and scikit-learn, and can run on Databricks, cloud computing services, and local machines.

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Humanloop

Another alternative is Humanloop, which is geared specifically for Large Language Model (LLM) development. It offers a collaborative environment for building and iterating on AI features, with tools for prompt management, evaluation and model optimization. Humanloop supports popular LLM providers and offers SDKs for easy integration, so it's a good choice for product teams and developers who want to speed up AI development and collaboration.

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HoneyHive

If you're more focused on AI evaluation and observability, HoneyHive is another option. It's an environment for AI development, testing and evaluation that includes features like automated CI testing, prompt management and production pipeline monitoring. HoneyHive supports more than 100 models and offers several pricing tiers, including a free option for individual developers and researchers.

More Alternatives to Weights & Biases

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Freeplay

Streamline large language model product development with a unified platform for experimentation, testing, monitoring, and optimization, accelerating development velocity and improving quality.

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Dataloop

Unify data, models, and workflows in one environment, automating pipelines and incorporating human feedback to accelerate AI application development and improve quality.

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Openlayer

Build and deploy high-quality AI models with robust testing, evaluation, and observability tools, ensuring reliable performance and trustworthiness in production.

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Hugging Face

Explore and collaborate on over 400,000 models, 150,000 applications, and 100,000 public datasets across various modalities in a unified platform.

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Klu

Streamline generative AI application development with collaborative prompt engineering, rapid iteration, and built-in analytics for optimized model fine-tuning.

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LastMile AI

Streamline generative AI application development with automated evaluators, debuggers, and expert support, enabling confident productionization and optimal performance.

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Keywords AI

Streamline AI application development with a unified platform offering scalable API endpoints, easy integration, and optimized tools for development and monitoring.

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Athina

Experiment, measure, and optimize AI applications with real-time performance tracking, cost monitoring, and customizable alerts for confident deployment.

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Flowise

Orchestrate LLM flows and AI agents through a graphical interface, linking to 100+ integrations, and build self-driving agents for rapid iteration and deployment.

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TeamAI

Collaborative AI workspaces unite teams with shared prompts, folders, and chat histories, streamlining workflows and amplifying productivity.

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Airtrain AI

Experiment with 27+ large language models, fine-tune on your data, and compare results without coding, reducing costs by up to 90%.

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Langfuse

Debug, analyze, and experiment with large language models through tracing, prompt management, evaluation, analytics, and a playground for testing and optimization.

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Superpipe

Build, test, and deploy Large Language Model pipelines on your own infrastructure, optimizing results with multistep pipelines, dataset management, and experimentation tracking.

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PI.EXCHANGE

Build predictive machine learning models without coding, leveraging an end-to-end pipeline for data preparation, model development, and deployment in a collaborative environment.

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ThirdAI

Run private, custom AI models on commodity hardware with sub-millisecond latency inference, no specialized hardware required, for various applications.

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MonsterGPT

Fine-tune and deploy large language models with a chat interface, simplifying the process and reducing technical setup requirements for developers.

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Magicflow

Centralize generative AI model development and testing, streamlining collaboration and feedback across multidisciplinary teams with bulk generation, analysis, and rating features.

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AirOps

Create sophisticated LLM workflows combining custom data with 40+ AI models, scalable to thousands of jobs, with integrations and human oversight.

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Obviously AI

Automate data science tasks to build and deploy industry-leading predictive models in minutes, without coding, for classification, regression, and time series forecasting.

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Lamini

Rapidly develop and manage custom LLMs on proprietary data, optimizing performance and ensuring safety, with flexible deployment options and high-throughput inference.

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Vellum

Manage the full lifecycle of LLM-powered apps, from selecting prompts and models to deploying and iterating on them in production, with a suite of integrated tools.