Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Machine learning model serving framework with dynamic batching and pipelined stages, provides an easy-to-use Python interface.
Python-free Rust inference server with OpenAI API compatibility and hot model swapping.
An MLOps/LLMOps platform for model building, evaluation, and fine-tuning.
Suite of tools that users, both novice and advanced, can use to optimize machine learning models for deployment and execution.
Large Language Model Text Generation Inference.
Voice Models uses AI for speech, voice, transcription, music, or other audio workflows.
🔭 The Einstein AI model provides machine-learning models, research, training resources, or evaluation tools.
FastEdit aims to assist developers with injecting fresh and customized knowledge into large language models efficiently using one single command.
Edit /src/streamlit app.py to customize this app to your heart's desire.:heart:.
Juno crafts studies, leads interviews, and reveals the why — customer research run by AI.
Build, train, and ship custom machine learning models using an easy visual interface.
A low-code framework for building custom AI models like LLMs and other deep neural networks. opensource.
Continue - Open-source AI code assistant. Connect any model and any context to create custom autocomplete and chat experiences inside the IDE.
Google Speech Gen helps build, test, automate, or manage AI agents, prompts, models, and API workflows.
A machine learning / bayesian inference assigning attributes to objects.
Creates or edits images with generative models and visual controls.
Agenta supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Computationally efficient procedures for regularized estimation with the semiparametric additive hazards regression model.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Helps teams build, deploy, observe or operate machine-learning systems.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Open-source Python library enabling ML model inspection and interpretation.