Search Results for "open source tv" - Page 7
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Showing 395 open source projects for "open source tv"
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Qwen2.5-Math
A series of math-specific large language models of our Qwen2 series
...Unlike its predecessor Qwen2-Math, Qwen2.5-Math supports both Chain-of-Thought (CoT) reasoning and Tool-Integrated Reasoning (TIR) for solving math problems, and works in both Chinese and English. It is optimized for solving mathematical benchmarks and exams; the 72B-Instruct model achieves state-of-the-art results among open source models on many English and Chinese math tasks. -
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Tauric TradingAgents
Multi-Agents LLM Financial Trading Framework
Tauric TradingAgents is a multi-agent AI framework designed for financial analysis, strategy generation, and automated trading workflows. It coordinates multiple specialized agents that collaborate on tasks such as data analysis, signal generation, and risk evaluation. The system enables complex reasoning by distributing responsibilities across agents, improving decision-making quality. It supports integration with market data sources and trading environments for real-world application. The... -
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TokenSpeed
TokenSpeed is a speed-of-light LLM inference engine
...The project is focused on the specific needs of agentic systems, where latency, throughput, and efficient scheduling matter across many short or tool-heavy requests. It builds on ideas and components from the broader open-source inference ecosystem while presenting its own execution stack. TokenSpeed is useful for developers building local or server-side LLM infrastructure for agents, coding systems, and high-volume AI applications. Its main value is providing an inference layer optimized for fast token generation under practical agent workloads. -
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VLMEvalKit
Open-source evaluation toolkit of large multi-modality models (LMMs)
VLMEvalKit is an open-source evaluation toolkit designed for benchmarking large vision-language models that combine visual understanding with natural language reasoning. The toolkit provides a unified framework that allows researchers and developers to evaluate multimodal models across a wide range of datasets and standardized benchmarks with minimal setup. -
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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Context Engineering
A frontier, first-principles handbook
Context Engineering is a comprehensive, open-source project serving as a first-principles handbook for the emerging discipline of context design and optimization in AI. Moving beyond traditional prompt engineering, this repository defines and explores how to craft and provide complete context payloads — not just single prompts — to large language models so they can perform tasks more reliably and intelligently. -
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SentenceTransformers
Multilingual sentence & image embeddings with BERT
SentenceTransformers is a Python framework for state-of-the-art sentence, text and image embeddings. The initial work is described in our paper Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. You can use this framework to compute sentence / text embeddings for more than 100 languages. These embeddings can then be compared e.g. with cosine-similarity to find sentences with a similar meaning. This can be useful for semantic textual similar, semantic search, or paraphrase... -
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LLM Telegram Bot
A Telegram bot for Large Language Models
LLM Telegram Bot is a self-hosted Telegram chatbot that connects messaging interactions with large language models, typically powered by Ollama or similar backends. The project is designed to provide a customizable AI assistant that can operate within Telegram conversations, supporting dynamic responses based on user input and configurable parameters. It includes features such as conversation memory, allowing the bot to maintain context across multiple messages and provide more coherent... -
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PEFT
State-of-the-art Parameter-Efficient Fine-Tuning
Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters. Fine-tuning large-scale PLMs is often prohibitively costly. In this regard, PEFT methods only fine-tune a small number of (extra) model parameters, thereby greatly decreasing the computational and storage costs. Recent State-of-the-Art PEFT techniques achieve performance comparable to that of full... -
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tldw Server
Your Personal Research Multi-Tool
tldw-server (mirror) is a mirrored distribution of an open-source backend service designed to store, process, and serve summarized information extracted from long pieces of content. The name “tldw” reflects the phrase “too long; didn’t watch,” which refers to tools that condense lengthy videos, articles, or documents into concise summaries. The server component typically acts as the core infrastructure that manages summaries, metadata, and retrieval operations for client applications or user interfaces. ... -
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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NBA Sports Betting Machine Learning
NBA sports betting using machine learning
NBA-Machine-Learning-Sports-Betting is an open-source Python project that applies machine learning techniques to predict outcomes of National Basketball Association games for analytical and betting-related research. The system gathers historical team statistics and game data spanning multiple seasons, beginning with the 2007–2008 NBA season and continuing through the present. -
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GPT-API-free
Free ChatGPT&DeepSeek API Key
GPT-API-free is a project that provides access to GPT-style APIs without requiring direct integration with paid official endpoints, focusing on accessibility and ease of experimentation. It offers a proxy-based approach that allows developers to interact with language models through a simplified interface, often requiring minimal configuration. The system is designed to lower barriers for developers who want to test or build applications using conversational AI without managing billing or... -
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OpenPlanter
Language-model investigation agent with a terminal UI
OpenPlanter is an open-source Python project focused on building an intelligent automated planting or gardening system powered by software control and data processing. The repository is designed to help developers and hobbyists create programmable plant management workflows that can monitor, schedule, and optimize growing conditions. It emphasizes automation and extensibility, allowing integration with sensors, environmental data, and control logic for smart cultivation setups. ... -
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files-to-prompt
Concatenate a directory full of files into a single prompt
files-to-prompt is a Python command-line tool that takes one or more files or entire directories and concatenates their contents into a single, LLM-friendly prompt. It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It... -
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ChatGLM3
ChatGLM3 series: Open Bilingual Chat LLMs | Open Source Bilingual Chat
ChatGLM3 is ZhipuAI & Tsinghua KEG’s third-gen conversational model suite centered on the 6B-parameter ChatGLM3-6B. It keeps the series’ smooth dialog and low deployment cost while adding native tool use (function calling), a built-in code interpreter, and agent-style workflows. The family includes base and long-context variants (8K/32K/128K). The repo ships Python APIs, CLI and web demos (Gradio/Streamlit), an OpenAI-format API server, and a compact fine-tuning kit. Quantization (4/8-bit),... -
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Youtu-GraphRAG
Vertically Unified Agents for Graph Retrieval-Augmented Reasoning
Youtu-GraphRAG is a research framework developed by Tencent for performing complex reasoning using graph-based retrieval-augmented generation. The system combines knowledge graphs, retrieval mechanisms, and agent-based reasoning into a unified architecture designed to handle knowledge-intensive tasks. Instead of relying solely on text retrieval, the framework organizes information into structured graph schemas that represent entities, relationships, and attributes. These structures allow the... -
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vim-ai
AI-powered code assistant for Vim. OpenAI and ChatGPT plugin for Vim
vim-ai is an AI-powered assistant plugin for Vim and Neovim that brings language-model features directly into the editor. It allows users to generate code or text, edit selections in place, and carry on interactive chat-style conversations without leaving the terminal editing environment. The plugin is built around OpenAI-compatible APIs, which means it can work not only with OpenAI itself but also with compatible proxies and alternative providers. Its command set covers text completion,... -
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Xtuner
A Next-Generation Training Engine Built for Ultra-Large MoE Models
Xtuner is a large-scale training engine designed for efficient training and fine-tuning of modern large language models, particularly mixture-of-experts architectures. The framework focuses on enabling scalable training for extremely large models while maintaining efficiency across distributed computing environments. Unlike traditional 3D parallel training strategies, XTuner introduces optimized parallelism techniques that simplify scaling and reduce system complexity when training massive... -
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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters... -
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Infinity
Low-latency REST API for serving text-embeddings
Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. Infinity is developed under MIT License. Infinity powers inference behind Gradient.ai and other Embedding API providers. -
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RecAI
Bridging LLM and Recommender System
RecAI is an open-source research platform developed by Microsoft to explore how large language models can be integrated into modern recommender systems. Traditional recommender systems rely on structured behavioral data such as user interactions and item embeddings, while large language models excel at understanding language and reasoning about user preferences. -
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MiniOneRec
Minimal reproduction of OneRec
MiniOneRec is an open-source framework designed to explore generative approaches to recommendation systems using large language model architectures. Traditional recommender systems typically rely on large embedding tables and ranking models, but MiniOneRec adopts a generative paradigm in which items are represented as sequences of semantic identifiers generated by autoregressive models. -
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FuzzyAI Fuzzer
A powerful tool for automated LLM fuzzing
FuzzyAI is an open-source fuzzing framework designed to test the security and reliability of large language model applications. The tool automates the process of generating adversarial prompts and input variations to identify vulnerabilities such as jailbreaks, prompt injections, or unsafe model responses. It allows developers and security researchers to systematically evaluate the robustness of LLM-based systems by simulating a wide range of malicious or unexpected inputs. ... -
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SageAttention
NeurIPS2025 Spotlight] Quantized Attention
SageAttention is an open-source optimization library designed to accelerate the attention mechanism used in transformer-based neural networks. 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. -
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LMOps
General technology for enabling AI capabilities w/ LLMs and MLLMs
LMOps is a research initiative and open-source toolkit focused on the development and operational management of AI applications built with large language models and generative AI systems. The project explores the technologies and methodologies required to move foundation models from research environments into production-grade AI products. It includes experimental tools and frameworks that help developers optimize prompts, design workflows for generative models, and manage the lifecycle of LLM-based systems. ... -
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MiniMax-01
Large-language-model & vision-language-model based on Linear Attention
MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel...
