Search Results for "low level"
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33 projects for "low level" with 2 filters applied:
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AsmJit
Low-latency machine code generation
...It is commonly used in applications such as emulators, compilers, and high-performance computing systems where runtime optimization is essential. asmjit emphasizes low latency and efficiency, ensuring that generated code executes quickly without significant overhead. Its modular design allows developers to integrate it into various systems with minimal friction. Overall, asmjit bridges the gap between high-level programming and low-level execution by enabling efficient runtime code generation. -
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tt-metal
TT-NN operator library, and TT-Metalium low level kernel programming
tt-metal, also referred to in its documentation as TT-Metalium, is Tenstorrent’s low-level software development kit for programming applications on Tenstorrent AI accelerators. The project is designed for developers who need direct access to the company’s Tensix processor architecture, exposing a programming model that is closer to hardware control than high-level inference frameworks. Instead of following a traditional GPU model centered on massive thread parallelism, the platform is built around a grid of specialized compute nodes called Tensix cores, each with local SRAM, dedicated compute units, and multiple RISC-V control processors. ... -
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wllama
WebAssembly binding for llama.cpp - Enabling on-browser LLM inference
...By running models locally on the user’s device, wllama enables privacy-preserving AI applications that do not require sending data to remote servers. The framework provides both high-level APIs for common tasks such as text generation and embeddings, as well as low-level APIs that expose tokenization, sampling controls, and model state management. -
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ggml
Tensor library for machine learning
ggml is an open-source tensor library designed for efficient machine learning computation with a focus on running models locally and with minimal dependencies. Written primarily in C and C++, the library provides low-level tensor operations and automatic differentiation that allow developers to implement machine learning algorithms and neural networks efficiently. The project emphasizes portability and performance, enabling machine learning inference across a wide range of hardware environments including CPUs and specialized accelerators. It is widely used as a foundational component in projects that run large language models locally, including tools that perform inference for transformer-based models. ... -
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LTX-2
Python inference and LoRA trainer package for the LTX-2 audio–video
...The framework targets both interactive graphical applications and media-rich experiences, making it a solid foundation for games, creative tools, or visualization systems that demand both performance and flexibility. While being low-level, it also provides sensible defaults and helper abstractions that reduce boilerplate and help teams maintain clear, maintainable code. -
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tiny-llm
A course of learning LLM inference serving on Apple Silicon
...The project is structured as a guided course that walks developers through the process of implementing the core components required to run a modern language model, including attention mechanisms, token generation, and optimization techniques. Rather than relying on high-level machine learning frameworks, the codebase uses mostly low-level array and matrix manipulation APIs so that developers can understand exactly how model inference works internally. The project demonstrates how to load and run models such as Qwen-style architectures while progressively implementing performance improvements like KV caching, request batching, and optimized attention mechanisms. ... -
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ByteHook
ByteHook is an Android PLT hook library
ByteHook is a ByteDance-hosted project whose name suggests a hooking or instrumentation library, likely used for hooking system calls or API calls for monitoring, sandboxing or instrumentation. The repository appears to aim at low-level hooking/injection capabilities, perhaps to support runtime introspection, behavioral monitoring, or hooking-based instrumentation (e.g. for security, tracing, sandboxing, or debugging). Because hooking is a common technique for intercepting library or system calls, Bhook likely provides abstractions to inject hooks into processes or libraries, enabling custom behavior monitoring or modification — which can be useful for building security tools, monitoring frameworks, or dynamic instrumentation. ... -
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whisper.cpp
Port of OpenAI's Whisper model in C/C++
whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples.... -
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hls4ml
Machine learning on FPGAs using HLS
hls4ml is an open-source framework that enables machine learning models to be implemented directly on hardware such as FPGAs and ASICs using high-level synthesis techniques. The system converts trained neural network models from common machine learning frameworks into hardware description code suitable for ultra-low-latency inference. This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast response times and minimal power consumption. ... -
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JEPA
PyTorch code and models for V-JEPA self-supervised learning from video
JEPA (Joint-Embedding Predictive Architecture) captures the idea of predicting missing high-level representations rather than reconstructing pixels, aiming for robust, scalable self-supervised learning. A context encoder ingests visible regions and predicts target embeddings for masked regions produced by a separate target encoder, avoiding low-level reconstruction losses that can overfit to texture. This makes learning focus on semantics and structure, yielding features that transfer well with simple linear probes and minimal fine-tuning. ... -
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ManiSkill
SAPIEN Manipulation Skill Framework
...Developed by Hao Su Lab, it focuses on robotic manipulation with diverse, high-quality 3D tasks designed to challenge perception, control, and planning in robotics. ManiSkill provides both low-level control and visual observation spaces for realistic learning scenarios. -
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FastRTC
The python library for real-time communication
...FastRTC also integrates nicely with UI frameworks (e.g. via a web demo using Gradio), so developers can rapidly prototype and deploy real-time streaming applications without deep knowledge of low-level WebRTC internals. Because voice-enabled AI agents often involve many moving parts (speech-to-text, text processing, text-to-speech, streaming, session/chat management), FastRTC helps by handling the streaming aspect, leaving the rest to be plugged in modularly. -
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Magnitude
Vision AI browser agent for automation, testing, and extraction
...Developers can use it to automate repetitive web tasks, integrate services without APIs, or build advanced browser-based agents. It also provides flexible abstraction levels, allowing both high-level task execution and precise low-level control of actions like mouse movements and keyboard input. -
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OuteTTS
Interface for OuteTTS models
OuteTTS is an interface library for running OuteTTS text-to-speech models across a range of backends, making it easier to deploy the same model on different hardware and runtimes. It provides a high-level Interface API that wraps model configuration, speaker handling, and audio generation so you can focus on integrating speech into your application rather than wiring up low-level engines. The project supports multiple backends including llama.cpp (Python bindings and server), Hugging Face Transformers, ExLlamaV2, VLLM and a JavaScript interface via Transformers.js, allowing it to run on CPUs, NVIDIA CUDA GPUs, AMD ROCm, Vulkan-capable GPUs, and Apple Metal. ... -
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WhisperJAV
Uses Qwen3-ASR, local LLM, Whisper, TEN-VAD
WhisperJAV is an open-source speech transcription pipeline designed specifically for generating subtitles for Japanese adult video content. The project addresses challenges that standard speech recognition models face when transcribing this type of audio, which often includes low signal-to-noise ratios and large numbers of non-verbal vocalizations. Traditional automatic speech recognition systems can misinterpret these sounds as words, leading to inaccurate transcripts. WhisperJAV introduces... -
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Softaworks Agent Skills
A curated collection of skills for AI coding agents
...The toolkit’s modular design follows the Agent Skills format, making it easy for users to install only what’s needed via CLI installers or plugin marketplaces. Because the set spans from low-level utilities like dependency updaters to higher-level planning and communication aids, it can streamline many aspects of a developer’s day-to-day work. -
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ds4.c
DeepSeek 4 Flash local inference engine for Metal
...The engine includes DS4-specific model loading, KV cache management, prompt rendering, and OpenAI-compatible server APIs for local deployment workflows. Built as a native low-level implementation, it focuses on performance, reduced abstraction overhead, and direct integration with Apple GPU acceleration through Metal compute graphs. The project also supports streaming inference behavior and local API serving for integration with external tools and AI applications. Overall, ds4 represents a minimalist high-performance approach to running large language models locally without relying on heavyweight inference frameworks. -
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Groq Python
The official Python Library for the Groq API
Groq Python is the official Python SDK for the Groq REST API, giving Python developers straightforward access to Groq’s LLM, chat, audio, and other AI services. Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and... -
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Anthropic's Original Performance
Anthropic's original performance take-home, now open for you to try
Anthropic's Original Performance repository contains the publicly released version of a performance challenge originally used by Anthropic as part of their technical interview process, offering developers the opportunity to optimize and benchmark low-level code against simulated models. The project sets up a baseline performance problem where participants work to reduce simulated “clock cycles” required to run a given workload, effectively challenging them to engineer faster code under constraints. This take-home includes starter code, tests, and tools to debug performance, aiming to measure how effectively one can apply algorithmic improvements and optimizations. ... -
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OpenAI Realtime Embedded
Instructions on how to use the Realtime API on Microcontrollers
openai-realtime-embedded is a repository that provides resources, SDKs, and example links for using OpenAI’s Realtime API on embedded hardware platforms (e.g. microcontrollers). The goal is to enable low-latency conversational agents (e.g. voice-based assistants) running directly on constrained devices, by leveraging WebRTC and streaming APIs to communicate with OpenAI systems. The repo includes pointers to an ESP32 implementation (maintained as esp32 branch) and documentation that Espressif... -
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3FS
A high-performance distributed file system
The 3FS repository (standing likely for “Feature 3F System” or similar) is focused on providing a feature extraction and transformation framework tailored to deep and large models, especially in token-based systems. Its primary aim is to support efficient and scalable feature transformation pipelines—especially for inference environments—by batching, caching, and integrating feature-based modules like segmenters, sparse retrievers, and scorers seamlessly. The repo includes APIs to define... -
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Coinbase Agentic Wallet Skills
npx skills add coinbase/agentic-wallet-skills
...It provides a set of pre-built “skills” that abstract complex blockchain interactions into simple, callable capabilities, allowing agents to authenticate, manage funds, and execute transactions without requiring developers to implement low-level logic. These skills are designed to integrate seamlessly with the awal CLI and agent frameworks, enabling rapid deployment of wallet-enabled AI systems with minimal setup. The architecture is centered on composability, where each skill represents a discrete capability such as sending stablecoins, trading tokens, or interacting with paid APIs. ... -
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Preline UI
Preline UI is an open-source set of prebuilt UI components
...It includes a rich collection of components such as buttons, navigation bars, dropdowns, modals, form controls, and more that are styled using Tailwind’s utility classes and are easy to customize without writing low-level CSS. Developers can quickly assemble complex, mobile-friendly user interfaces with consistent design and behavior straight out of the box, greatly reducing the overhead of crafting common UI patterns from scratch. Preline also offers setup guidance and integration examples so teams can get started rapidly within their Tailwind projects. ... -
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Bard
Python SDK/API for reverse engineered Google Bard
...Because Google doesn’t provide a standard public API for Bard, this project works by reverse-engineering the web interactions that power Bard’s interface and exposing them through code-friendly interfaces, enabling chat automation, custom workflows, and bot creation. The repository typically includes authentication handling, session management, and request/response serialization so that developers don’t have to deal with low-level HTTP details. Users can integrate Bard into Python scripts, chatbots, or local testing environments where conversational AI is useful but an official API isn’t yet available. -
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godlp
Sensitive information protection toolkit
godlp appears to be another software project from ByteDance — however, as of the most recent checks, there’s very little publicly available information about it: the repository exists under ByteDance’s GitHub, but its documentation, README, and metadata are minimal (or not human-readable), and the project seems to have limited community visibility compared to their other major tools. Because of that opacity, one must infer that godlp is likely a specialized internal or early-stage tool,...
