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1,313 | 59,531 | The Python programming language | |
234 | 2,720 | Oils is our upgrade path from bash to a better language and runtime. It's also for Python and JavaScript users who avoid shell! | |
184 | 52,603 | Inference code for Llama models | |
121 | 8,263 | SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Users are neither tracked nor profiled. | |
114 | 18,257 | Project documentation with Markdown. | |
75 | 30,639 | LlamaIndex is a data framework for your LLM applications | |
29 | 7,800 | Large Language Model Text Generation Inference | |
24 | 8,869 | WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization) | |
12 | 74 | the main Llama 3 GitHub site - will be moved under Meta-Llama | |
10 | 316 | Inference engine powering open source models on OpenRouter | |
8 | 15,787 | Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective. Devika aims to be a competitive open-source alternative to Devin by Cognition AI. | |
7 | 22,123 | 🐚 OpenDevin: Code Less, Make More | |
6 | 5,516 | RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. | |
6 | 823 | Open-source solution designed to automate the process of verifying factuality | |
6 | 403 | Powering AWS purpose-built machine learning chips. Blazing fast and cost effective, natively integrated into PyTorch and TensorFlow and integrated with your favorite AWS services | |
6 | 78 | Python & JS SDK for building custom code interpreters. Built with E2B - Cloud Runtime for AI Agents. | |
5 | 1,792 | A project structure aware autonomous software engineer aiming for autonomous program improvement. Resolved 15.95% tasks in full SWE-bench | |
5 | 336 | ||
5 | 90 | No-code LLM Platform to launch APIs and ETL Pipelines to structure unstructured documents | |
4 | 9,415 | SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.29% of bugs in the SWE-bench evaluation set and takes just 1.5 minutes to run. |
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