GitHub · Change is constant. GitHub keeps you ahead.
Whether you’re scaling your development process or just learning how to code, GitHub is where you belong. Join the world’s most …
Sign in to GitHub · GitHub
GitHub is where people build software. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million …
GitHub - LinkedIn
The home of software development | As the global home for all developers, GitHub is the complete AI-powered developer platform to …
Download GitHub Desktop
Download GitHub Desktop Focus on what matters instead of fighting with Git. Whether you're new to Git or a seasoned user, GitHub …
What Is GitHub? Use Cases and FAQ - Coursera
Jun 27, 2026 · GitHub is a cloud-based platform that hosts Git repositories and adds collaboration tools on top of Git. It allows teams …
GitHub - Wikipedia
GitHub, headquartered in San Francisco, is operated by Github, Inc., a subsidiary of Microsoft since 2018. [10] It is commonly used to …
Home - The GitHub Blog
Updates, ideas, and inspiration from GitHub to help developers build and design software.
What is GitHub? More than Git version control in the cloud
Sep 6, 2024 · GitHub makes it easy to find useful code, copy repositories for your own use, and submit changes to others’ projects.
GitHub Universe 2026
Join us for the opening keynote, where we'll kick things off with our latest product announcements, live demos, and maybe a few …
GitHub Changelog
1 day ago · Your source for the latest features, improvements, and fixes across GitHub products, all in one place.
GitHub - embeddings-benchmark/mteb: MTEB: State-of-the-art evaluation ...
MTEB was introduced in "MTEB: Massive Text Embedding Benchmark", and heavily expanded in "MMTEB: Massive Multilingual Text Embedding Benchmark". When using mteb, we recommend that you cite both articles.
Massive Text Embedding Benchmark - GitHub
MTEB is a Python framework for evaluating embeddings and retrieval systems for both text and image. MTEB covers more than 1000 languages and diverse tasks, from classics like classification and clustering to use-case specialized tasks such as legal, code, or healthcare retrieval.…
MTEB - Massive Text Embedding Benchmark
MTEB Info We recently released mteb version 2.0.0, to see what is new check of what is new and see how to upgrade your existing code. Welcome documentation of MTEB. mteb a package for benchmark and evaluating the quality of embeddings. MTEB is the go-to documentation for evaluati…
mteb (Massive Text Embedding Benchmark) - Hugging Face
Massive Text Embeddings Benchmark Audio-visual video embedding quality across retrieval, classification, clustering, pair classification, zero-shot classification, and video-centric...
mteb (Massive Text Embedding Benchmark) - Hugging Face
Massive Text Embeddings Benchmark Muennighoff submitted a paper about 10 hours ago
MTEB: Massive Text Embedding Benchmark - ACL Anthology
To solve this problem, we introduce the Massive Text Embedding Benchmark (MTEB). MTEB spans 8 embedding tasks covering a total of 58 datasets and 112 languages. Through the benchmarking of 33 models on MTEB, we establish the most comprehensive benchmark of text embeddings todate.
Overview - Massive Text Embedding Benchmark - docs.mteb.org
A benchmark is a tool to evaluate an embedding model for a given use case. For instance, mteb (eng) is intended to evaluate the quality of text embedding models for broad range of English use-cases such retrieval, classification, and reranking.
embeddings-benchmark/mteb | DeepWiki
What is MTEB? MTEB (Massive Text Embedding Benchmark) is a comprehensive open-source framework designed to evaluate embedding models across a wide variety of tasks, languages, and modalities. It facilitates standardized, reproducible benchmarking of embedding quality for text and…
[2210.07316] MTEB: Massive Text Embedding Benchmark - arXiv.org
To solve this problem, we introduce the Massive Text Embedding Benchmark (MTEB). MTEB spans 8 embedding tasks covering a total of 58 datasets and 112 languages. Through the benchmarking of 33 models on MTEB, we establish the most comprehensive benchmark of text embeddings to date…
MMTEB: Massive Multilingual Text Embedding Benchmark
Text embeddings are typically evaluated on a narrow set of tasks, limited in terms of languages, domains, and task types. To circumvent this limitation and to provide a more comprehensive evaluation, we introduce the Massive Multilingual Text Embedding Benchmark (MMTEB) -- a larg…