Search Results for "transfer function model" - Page 4
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Showing 414 open source projects for "transfer function model"
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Brick
A declarative Unix terminal UI library written in Haskell
Brick is a Haskell terminal user interface (TUI) programming toolkit that enables developers to build rich, responsive terminal applications via a declarative model: you define a pure function that renders the UI from application state and supply state transition logic to handle events. brick exposes a declarative API. Unlike most GUI toolkits which require you to write a long and tedious sequence of widget creations and layout setup, brick just requires you to describe your interface using a set of declarative layout combinators. ... -
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Stagehand
An AI web browsing framework focused on simplicity and extensibility
...The goal of Stagehand is to provide a lightweight, configurable framework, without overly complex abstractions, as well as modular support for different models and model providers. It's not going to order you a pizza, but it will help you reliably automate the web. Each Stagehand function takes in an atomic instruction, such as act("click the login button") or extract("find the red shoes"), generates the appropriate Playwright code to accomplish that instruction, and executes it. -
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AWS Lambda for Go
Libraries, samples and tools to help Go developers develop AWS Lambda
Libraries, samples and tools to help Go developers develop AWS Lambda functions. Libraries, samples, and tools to help Go developers develop AWS Lambda functions. Preparing a binary to deploy to AWS Lambda requires that it is compiled for Linux and placed into a .zip file. Windows developers may have trouble producing a zip file that marks the binary as executable on Linux. To create a .zip that will work on AWS Lambda, the build-lambda-zip tool may be helpful. -
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Pocket TTS
A TTS that fits in your CPU (and pocket)
Pocket TTS is a lightweight text-to-speech project designed to run efficiently on CPUs, targeting developers who want local speech generation without depending on GPUs or hosted web APIs. It is built to feel practical in everyday applications, where installation and usage should be as simple as adding a dependency and calling a function. The project focuses on keeping the runtime footprint manageable while still producing natural-sounding speech, which makes it attractive for offline tools,... -
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Prophet
Tool for producing high quality forecasts for time series data
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal... -
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CoreDNS
CoreDNS is a DNS server that chains plugins
...Retrieve zone data from primaries, i.e., act as a secondary server (AXFR only) (secondary). Sign zone data on-the-fly (dnssec). Load balancing of responses (loadbalance). Allow for zone transfers, i.e., act as a primary server (file + transfer). Automatically load zone files from disk (auto). -
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ChatGPT Java API
Java SDK for seamless integration with ChatGPT APIs
ChatGPT-Java is a Java SDK created by PlexPt that offers a convenient, out-of-the-box integration with the OpenAI ChatGPT API (including models like GPT-4o, GPT-5) for Java applications. The library supports chat completions, token counting, function calls, streaming responses, proxy configuration, custom API host, and integration with frameworks such as Spring (via SseEmitter). It abstracts the HTTP interaction and JSON parsing into simple Java objects and builders while handling details like token usage and model selection. It is published to Maven Central under the group com.github.plexpt, e.g., version 5.0.1. ... -
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DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning,...
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Mediary Scout
Agent-driven media library for your cloud drives
Mediary Scout is an agent-driven media library that acquires movies, television shows, and anime for supported cloud drives. An LLM agent searches connected indexers, selects a result according to quality and subtitle preferences, transfers it, and verifies what arrived. The library tracks season coverage, missing episodes, airing status, and scheduled gap-filling tasks. It supports 115, Quark, and GuangYaPan as separate workspaces without requiring local media downloads. Users can run an... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Real-Time Voice Cloning
Clone a voice in 5 seconds to generate arbitrary speech in real-time
Real-Time Voice Cloning is an influential deep-learning repository that demonstrates how to clone a voice from just a few seconds of audio and then generate arbitrary speech in that voice in near real time. It implements the SV2TTS pipeline (“Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis”) in three stages: a speaker encoder, a synthesizer, and a vocoder. In the first stage, short audio clips are converted into a fixed-dimensional speaker embedding that... -
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SpaceWasm
A flight-compliant WebAssembly interpreter
SpaceWasm is a NASA JPL WebAssembly interpreter designed for resource-constrained spacecraft systems. It implements a constrained form of the WebAssembly 1.0 specification for executing portable onboard programs. A streaming decoder reads modules in chunks, validates them in one pass, and converts instructions into an interpretation-focused intermediate representation. Its custom memory model uses fixed-size pages to provide deterministic allocation behavior and avoid panic on allocation... -
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Boulder
An ACME-based certificate authority, written in Go
...The ACME protocol allows the CA to automatically verify that an applicant for a certificate actually controls an identifier, and allows domain holders to issue and revoke certificates for their domains. Boulder is the software that runs Let's Encrypt. This component model lets us separate the function of the CA by security context. The Web Front End, Validation Authority, OCSP Responder and Publisher need access to the Internet, which puts them at greater risk of compromise. The Registration Authority can live without Internet connectivity, but still needs to talk to the Web Front End and Validation Authority. ... -
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Headroom
Compress tool outputs, logs, files, and RAG chunks
Headroom is a context optimization layer for LLM applications that compresses information before it reaches the model. It sits between an application and an LLM provider, intercepting requests and forwarding a shorter optimized prompt. The project is designed to reduce token usage while preserving the answer quality needed for agent workflows. It can compress tool outputs, logs, RAG chunks, files, and conversation history. Headroom can be used as a transparent proxy, a Python function, a TypeScript SDK, or through integrations with frameworks such as LangChain and LiteLLM. ... -
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Code-Mode
Plug-and-play library to enable agents to call MCP and UTCP tools
Code-Mode is a plug-and-play library that lets AI agents call tools by executing TypeScript (or via a Python wrapper) instead of making many individual function calls. Its core philosophy is that language models are very good at writing code, so rather than exposing hundreds of separate tool endpoints, you give the model a single “code execution” tool that has access to your full toolkit through code. This approach can dramatically reduce the number of tool-call iterations needed in complex workflows, turning multi-step call chains into a single code execution with internal branching and loops. ... -
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ispc
Intel SPMD Program Compiler
ispc is a compiler for a variant of the C programming language, with extensions for single programs, and multiple data programming. Under the SPMD model, the programmer writes a program that generally appears to be a regular serial program, though the execution model is actually that a number of program instances execute in parallel on the hardware. ispc compiles a C-based SPMD programming language to run on the SIMD units of CPUs and GPUs; it frequently provides a 3x or more speedup on... -
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Dive
Dive is an open-source MCP Host Desktop Application
Dive is an open‑source MCP host desktop application that serves as a bridge between MCP servers and any large language models supporting function calling, designed to deliver a seamless AI agent experience across environments. Compatible with ChatGPT, Anthropic, Ollama and OpenAI-compatible models. Enabling seamless MCP AI agent integration on both stdio and SSE mode. One-click access to managed MCP servers via OAPHub.ai - eliminates complex local deployments. Modern Tauri version alongside... -
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Z-BlogPHP
Z-BlogPHP blog program
Z-BlogPHP is a blog program provided by the Z-Blog community and has been committed to providing excellent blog writing experience to domestic users. The first edition has been released since 2005 and has a history of 18 years. It is one of the few open-source CMS systems that continue to provide updates in China. Our goal is to immerse users in writing and record life, without paying attention to cumbersome settings, etc., and let users focus on creation. For users, it is simple and easy to... -
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GPT PILOT
The first real AI developer
GPT PILOT is an open-source AI developer assistant designed to build full applications by collaborating with a human developer throughout the software lifecycle. Unlike simple autocomplete tools, it aims to function as a true AI engineer that can generate features, set up environments, debug code, and request feedback when necessary. The system works by asking clarifying questions, producing product requirements, and then implementing the application step by step while the user supervises.... -
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Lithops
A multi-cloud framework for big data analytics
Lithops is an open-source serverless computing framework that enables transparent execution of Python functions across multiple cloud providers and on-prem infrastructure. It abstracts cloud providers like IBM Cloud, AWS, Azure, and Google Cloud into a unified interface and turns your Python functions into scalable, event-driven workloads. Lithops is ideal for data processing, ML inference, and embarrassingly parallel workloads, giving you the power of FaaS (Function-as-a-Service) without... -
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DynamicHMC
Implementation of robust dynamic Hamiltonian Monte Carlo methods
Implementation of robust dynamic Hamiltonian Monte Carlo methods in Julia. In contrast to frameworks that utilize a directed acyclic graph to build a posterior for a Bayesian model from small components, this package requires that you code a log-density function of the posterior in Julia. Derivatives can be provided manually, or using automatic differentiation. Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent of coding a (log) posterior density in Julia. ... -
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InsForge
InsForge is the backend built for AI-assisted development
InsForge is an open-source backend development platform designed specifically for AI-assisted or agent-driven application development, positioning itself as an agent-native alternative to tools like Supabase by exposing backend primitives (auth, database, storage, serverless functions, and AI integrations) in a way that intelligent agents can understand, reason about, and act upon directly. Rather than forcing developers to manually cobble together authentication flows, database schemas,... -
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Fyrox
3D and 2D game engine written in Rust
...Built-in save/load, save or load entire state of the engine in one call. Full-featured scene graph with various nodes (pivot, camera, mesh, light, particle system, sprite). High-quality binaural sound with Head-Related Transfer Function (HRTF) support. Standalone scene editor makes scenes in native engine format using the power of rusty editor. Rigid bodies, rich set of various colliders, joints, ray casting, etc. -
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Neuron AI
The PHP Agentic Framework to build production-ready AI driven apps
...It is designed for developers who want to create systems such as RAG pipelines, multi-agent workflows, and business process automations without having to hand-build every integration from scratch. The framework provides an Agent class that can be extended to inherit core capabilities like memory, tools, function calling, and retrieval-augmented generation. Its design is modular, so developers can swap model providers with minimal changes to their application code, which makes it practical for teams that need flexibility across vendors. The project also supports structured output, monitoring, MCP connectivity, and workflow patterns that include human-in-the-loop intervention when automated flows need review or correction. -
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SageAttention
NeurIPS2025 Spotlight] Quantized Attention
...Since attention operations are often the most computationally expensive component of modern AI models, SageAttention introduces quantization techniques that significantly reduce computational overhead while preserving model accuracy. The system achieves this by using low-precision numerical formats such as INT4, FP8, or INT8 to represent key matrices within the attention computation. These optimizations allow models to perform matrix operations faster and consume less memory during inference. SageAttention is designed to function as a plug-and-play replacement for standard attention implementations, enabling developers to accelerate existing models without modifying their architecture. -
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Super comprehensive deep learning notes
Super Comprehensive Deep Learning Notes
Super comprehensive deep learning notes is a massive and well-structured collection of deep learning notebooks that serve as a comprehensive study resource for anyone wanting to learn or reinforce concepts in computer vision, natural language processing, deep learning architectures, and even large-model agents. The repository contains hundreds of Jupyter notebooks that are richly annotated and organized by topic, progressing from basic Python and PyTorch fundamentals to advanced neural network designs like ResNet, transformers, and object detection algorithms. It’s not just a dry code repository; it includes theoretical explanations alongside hands-on examples, loss function explorations, optimization routines, and full end-to-end experiments on real datasets, making it highly suitable for both self-study and classroom use.
