Search Results for "inference"
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Showing 134 open source projects for "inference"
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Mistral Inference
Official inference library for Mistral models
Open and portable generative AI for devs and businesses. We release open-weight models for everyone to customize and deploy where they want it. Our super-efficient model Mistral Nemo is available under Apache 2.0, while Mistral Large 2 is available through both a free non-commercial license, and a commercial license. -
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SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers, embedded, or automotive product platforms. ... -
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ONNX Runtime
ONNX Runtime: cross-platform, high performance ML inferencing
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Gen.jl
A general-purpose probabilistic programming system
An open-source stack for generative modeling and probabilistic inference. Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. -
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KServe
Standardized Serverless ML Inference Platform on Kubernetes
KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and... -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous compute infrastructure. ... -
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MegEngine
Easy-to-use deep learning framework with 3 key features
...On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference. -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. -
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BentoML
Unified Model Serving Framework
...Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference workloads to scale separately from the serving logic. Adaptive batching dynamically groups inference requests for optimal performance. Orchestrate distributed inference graph with multiple models via Yatai on Kubernetes. Easily configure CUDA dependencies for running inference with GPU. Automatically generate docker images for production deployment. -
11
AIMET
AIMET is a library that provides advanced quantization and compression
Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware accelerators. ... -
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NNCF
Neural Network Compression Framework for enhanced OpenVINO
NNCF (Neural Network Compression Framework) is an optimization toolkit for deep learning models, designed to apply quantization, pruning, and other techniques to improve inference efficiency. -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
...Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. This project is licensed under the Apache-2.0 License. Ensure you have access to an AWS account i.e. setup your environment such that awscli can access your account via either an IAM user or an IAM role. -
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AWS Neuron
Powering Amazon custom machine learning chips
AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. ... -
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AudioCraft
Audiocraft is a library for audio processing and generation
AudioCraft is a PyTorch library for text-to-audio and text-to-music generation, packaging research models and tooling for training and inference. It includes MusicGen for music generation conditioned on text (and optionally melody) and AudioGen for text-conditioned sound effects and environmental audio. Both models operate over discrete audio tokens produced by a neural codec (EnCodec), which acts like a tokenizer for waveforms and enables efficient sequence modeling. The repo provides inference scripts, checkpoints, and simple Python APIs so you can generate clips from prompts or incorporate the models into applications. ... -
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DocTR
Library for OCR-related tasks powered by Deep Learning
DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document... -
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XNNPACK
High-efficiency floating-point neural network inference operators
XNNPACK is a highly optimized, low-level neural network inference library developed by Google for accelerating deep learning workloads across a variety of hardware architectures, including ARM, x86, WebAssembly, and RISC-V. Rather than serving as a standalone ML framework, XNNPACK provides high-performance computational primitives—such as convolutions, pooling, activation functions, and arithmetic operations—that are integrated into higher-level frameworks like TensorFlow Lite, PyTorch Mobile, ONNX Runtime, TensorFlow.js, and MediaPipe. ... -
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MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
...AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers. AMD OpenVX is a highly optimized open-source implementation of the Khronos OpenVX™ 1.3 computer vision specification. It allows for rapid prototyping as well as fast execution on a wide range of computer hardware, including small embedded x86 CPUs and large workstation discrete GPUs. -
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ty
An extremely fast Python type checker and language server
...The tool is designed from the ground up to power editor integrations, enabling real-time feedback as developers write code with minimal latency. ty includes advanced type system capabilities such as intersection types, improved type inference, and detailed diagnostics that help identify issues even in partially typed codebases. It supports integration with multiple development environments through its language server implementation, providing features like code navigation, auto-completion, and inline hints. -
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OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
...Each agent runs inside a containerized sandbox governed by declarative YAML security policies that control network access, file permissions, and process behavior. The platform includes a gateway service that manages sandbox lifecycles and routes AI inference requests through controlled providers. OpenShell also features a privacy-aware routing system that prevents sensitive information from leaving the sandbox environment. By combining container isolation, policy enforcement, and agent orchestration, OpenShell offers a secure infrastructure for developing and operating AI agents. -
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pytype
A static type analyzer for Python code
...Documentation and a user guide detail configuration, supported features, and how inference interacts with modern Python idioms. -
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Zod
TypeScript-first schema validation with static type inference
TypeScript-first schema validation with static type inference. Zod is a TypeScript-first schema declaration and validation library. I'm using the term "schema" to broadly refer to any data type, from a simple string to a complex nested object. Zod is designed to be as developer-friendly as possible. The goal is to eliminate duplicative type declarations. With Zod, you declare a validator once and Zod will automatically infer the static TypeScript type. -
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Gitleaks
Protect and discover secrets using Gitleaks
Gitleaks is a fast, lightweight, portable, and open-source secret scanner for git repositories, files, and directories. With over 6.8 million docker downloads, 11.2k GitHub stars, 1.7 million GitHub Downloads, thousands of weekly clones, and over 400k homebrew installs, gitleaks is the most trusted secret scanner among security professionals, enterprises, and developers. Gitleaks-Action is our official GitHub Action. You can use it to automatically run a gitleaks scan on all your team's pull... -
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Temporal Inference Engine
A real time inference engine for temporal logical specifications
A real time inference engine for temporal logical specifications, which is able to acquire, process and generate any binary or real signal through POSIX IPC, files or UNIX sockets. Specifications of signals and dynamic systems are represented as special graphs and executed in real time, with a predictable sampling time of few milliseconds. Real time signal processing, dynamic system control, state machine modeling and logical property verification are some fields of application of this software. ... -
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DALI
A GPU-accelerated library containing highly optimized building blocks
...Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding, cropping, resizing, and many other augmentations. These data processing pipelines, which are currently executed on the CPU, have become a bottleneck, limiting the performance and scalability of training and inference. DALI addresses the problem of the CPU bottleneck by offloading data preprocessing to the GPU. Additionally, DALI relies on its own execution engine, built to maximize the throughput of the input pipeline.
