#embeddings

Integrate Atlassian Confluence Cloud with Amazon Quick

Artificial Intelligence Integrate Atlassian Confluence Cloud with Amazon Quick Teams can integrate Atlassian Confluence …

OpenAI feels “burned” by Apple’s crappy ChatGPT integration, insiders say

OpenAI is reportedly exploring legal options after Apple’s ChatGPT integration into its products didn’t live up to the A…

Granite Embedding Multilingual R2: Open Apache 2.0 Multilingual Embeddings with 32K Context — Best Sub-100M Retrieval Quality

Granite Embedding Multilingual R2: Open Apache 2.0 Multilingual Embeddings with 32K Context — Best Sub-100M Retrieval Qu…

Automate schema generation for intelligent document processing

Artificial Intelligence Automate schema generation for intelligent document processing Before you can extract informatio…

Announcing SAP’s strategic investment in n8n

Today we are announcing that SAP has invested in n8n. The investment values n8n at $5.2bn, more than double our valuatio…

Implementing advanced AI technologies in finance

Sponsored Implementing advanced AI technologies in finance Successful AI implementation requires shifts in workplace cul…

Manufacturing intelligence with Amazon Nova Multimodal Embeddings

Artificial Intelligence Manufacturing intelligence with Amazon Nova Multimodal Embeddings If you work in aerospace, auto…

In-Kernel Broadcast Optimization: Co-Designing Kernels for RecSys Inference

Featured projects TL;DR: - Traditional RecSys inference explicitly replicates shared user embeddings/sequences for every…

DeepInfra on Hugging Face Inference Providers 🔥

DeepInfra on Hugging Face Inference Providers 🔥 We're thrilled to share that DeepInfra is now a supported Inference Pro…

Power video semantic search with Amazon Nova Multimodal Embeddings

Artificial Intelligence Power video semantic search with Amazon Nova Multimodal Embeddings Video semantic search is unlo…

Optimize video semantic search intent with Amazon Nova Model Distillation on Amazon Bedrock

Artificial Intelligence Optimize video semantic search intent with Amazon Nova Model Distillation on Amazon Bedrock Opti…

Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers

Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers As a practical example, I'll w…

Multimodal Embedding & Reranker Models with Sentence Transformers

Multimodal Embedding & Reranker Models with Sentence Transformers Multimodal embedding models map inputs from different …

Build a Domain-Specific Embedding Model in Under a Day

Build a Domain-Specific Embedding Model in Under a Day With a single GPU and less than a day of training time, you can t…

Wayfair boosts catalog accuracy and support speed with OpenAI

Wayfair boosts catalog accuracy and support speed with OpenAI By embedding OpenAI models in supplier and catalog systems…

Multimodality Embeddings Bilge Yücel DevRel Engineer Stefano Fiorucci AI/Software Engineer Multimodal Search with Gemini Embedding 2 in Haystack Build multimodal search systems in Haystack using Gemini Embedding 2 to embed text, images, video, audio, and PDFs in a shared vector space. March 10, 2026

Multimodal Search with Gemini Embedding 2 in Haystack Build multimodal search systems in Haystack using Gemini Embedding…

Build Multi-Domain RAG Systems with Specialized Knowledge Bases

This Verified Node Spotlight was written by Jenna Pederson, Staff Developer Advocate for Pinecone. Imagine you manage mu…

Maximizing GPU Utilization with NVIDIA Run:ai and NVIDIA NIM

Organizations deploying LLMs are challenged by inference workloads with different resource requirements. A small embeddi…

Shaping the future of financial services

Morgan Stanley uses AI evals to shape the future of financial services Morgan Stanley(opens in a new window) collaborate…

Establishing a Scalable Sparse Ecosystem with the Universal Sparse Tensor

Sparse tensors are vectors, matrices, and higher-dimensional generalizations with many zeros. They are crucial in variou…

9/12/2025 Understanding Embeddings and Reranking at Scale

Retrieval-Augmented Generation has emerged as the dominant paradigm for grounding large language models with external kn…

OpenAI takes an ownership stake in Thrive Holdings to accelerate enterprise AI adoption

OpenAI takes an ownership stake in Thrive Holdings to accelerate enterprise AI adoption OpenAI and Thrive Holdings are p…

Diffusers welcomes FLUX-2

Welcome FLUX.2 - BFL’s new open image generation model 🤗 🚨 FLUX.2 is not meant to be a drop-in replacement of FLUX.1, …

Sentence Transformers is joining Hugging Face!

Sentence Transformers is joining Hugging Face! Sentence Transformers (a.k.a. SentenceBERT or SBERT) is a popular open-so…

10/9/2025 Announcing Embeddings and Reranking On Fireworks AI

Today, we're announcing a major upgrade to Fireworks for RAG workloads – we’re bringing the state-of-the-art Qwen3 8B Em…

Welcome EmbeddingGemma, Google's new efficient embedding model

Welcome EmbeddingGemma, Google's new efficient embedding model TL;DR Today, Google releases EmbeddingGemma, a state-of-t…

Arm & ExecuTorch 0.7: Bringing Generative AI to the masses

Arm & ExecuTorch 0.7: Bringing Generative AI to the masses With Arm’s recent SME2 announcement, the role of Arm KleidiAI…

Training and Finetuning Sparse Embedding Models with Sentence Transformers

Training and Finetuning Sparse Embedding Models with Sentence Transformers Finetuning sparse embedding models involves s…

Cohere on Hugging Face Inference Providers 🔥

Cohere on Hugging Face Inference Providers 🔥 We're thrilled to share that Cohere is now a supported Inference Provider …

Prefill and Decode for Concurrent Requests - Optimizing LLM Performance

Prefill and Decode for Concurrent Requests - Optimizing LLM Performance At TNG, we are self-hosting numerous Large Langu…

1 Billion Classifications

1 Billion Classifications These tasks often use encoder models, which are much smaller than modern LLMs, but at the 1B+ …

Train 400x faster Static Embedding Models with Sentence Transformers

Train 400x faster Static Embedding Models with Sentence Transformers TL;DR This blog post introduces a method to train s…

Visual Document Retrieval Goes Multilingual

Visual Document Retrieval Goes Multilingual TL;DR: We presentvdr-2b-multi-v1 , the best multilingual embedding model for…

Text-Conditional JEPA for Learning Semantically Rich Visual Representations

Text-Conditional JEPA for Learning Semantically Rich Visual Representations AuthorsChen Huang, Xianhang Li, Vimal Thilak…

Faster Text Generation with Self-Speculative Decoding

Faster Text Generation with Self-Speculative Decoding This technique not only speeds up text generation, but it also ach…

The 5 Most Under-Rated Tools on Hugging Face

The 5 Most Under-Rated Tools on Hugging Face The Hugging Face Hub allows broad usage since you have diverse hardware, an…

How we leveraged distilabel to create an Argilla 2.0 Chatbot

How we leveraged distilabel to create an Argilla 2.0 Chatbot TL;DR Discover how to build a Chatbot for a tool of your ch…

XLSCOUT Unveils ParaEmbed 2.0: a Powerful Embedding Model Tailored for Patents and IP with Expert Support from Hugging Face

XLSCOUT Unveils ParaEmbed 2.0: a Powerful Embedding Model Tailored for Patents and IP with Expert Support from Hugging F…

Diffusers welcomes Stable Diffusion 3

🧨 Diffusers welcomes Stable Diffusion 3 The model released today is Stable Diffusion 3 Medium, with 2B parameters. As p…

Introducing the Hugging Face Embedding Container for Amazon SageMaker

Introducing the Hugging Face Embedding Container for Amazon SageMaker In this Blog we will show you how to deploy open E…

Training and Finetuning Embedding Models with Sentence Transformers

Training and Finetuning Embedding Models with Sentence Transformers Finetuning Sentence Transformers involves several co…

A Brief Overview of Gender Bias in AI

AI models reflect, and often exaggerate, existing gender biases from the real world. It is important to quantify such bi…

Embedding models April 8, 2024 Embedding models are available in Ollama, making it easy to generate vector embeddings for use in search and retrieval augmented generation (RAG) applications.

Embedding models April 8, 2024 Ollama supports embedding models, making it possible to build retrieval augmented generat…

Blazing Fast SetFit Inference with 🤗 Optimum Intel on Xeon

Blazing Fast SetFit Inference with 🤗 Optimum Intel on Xeon SetFit achieves high accuracy with little labeled data - for…

Binary and Scalar Embedding Quantization for Significantly Faster & Cheaper Retrieval

Binary and Scalar Embedding Quantization for Significantly Faster & Cheaper Retrieval Table of Contents - Why Embeddings…

Enterprise-ready trust and safety

Salesforce Salesforce integrates OpenAI’s enterprise-ready LLMs to transform customer applications. Salesforce turned to…

Embedding AI into developer software

JetBrains JetBrains uses OpenAI’s API to build its fastest-growing product ever. JetBrains(opens in a new window) create…

CPU Optimized Embeddings with 🤗 Optimum Intel and fastRAG

CPU Optimized Embeddings with 🤗 Optimum Intel and fastRAG In this blog, we will show how to unlock significant performa…

Do text embeddings perfectly encode text?

The rise of the vector database As a result of the rapid advancement of generative AI in recent years, many companies ar…

🪆 Introduction to Matryoshka Embedding Models

🪆 Introduction to Matryoshka Embedding Models Additionally, we will provide practical guidance on how to use Matryoshka…

New embedding models and API updates

We are releasing new models, reducing prices for GPT‑3.5 Turbo, and introducing new ways for developers to manage API ke…

Using open-source models for faster and cheaper text embeddings

Using open-source models for faster and cheaper text embeddings Embeddings are a powerful tool for working with text. By…

Interactively explore your Huggingface dataset with one line of code

Interactively explore your Huggingface dataset with one line of code Renumics Spotlight allows you to create interactive…

Deploy Embedding Models with Hugging Face Inference Endpoints

Deploy Embedding Models with Hugging Face Inference Endpoints Compared to LLMs are Embedding Models smaller in size and …

How to use retrieval augmented generation with ChromaDB and Mistral

How to use retrieval augmented generation with ChromaDB and Mistral Over the last few months, Retrieval Augmented Genera…

Welcome fastText to the Hugging Face Hub

Welcome fastText to the Hugging Face Hub To speed up computation, fastText uses hierarchical softmax, capitalizing on th…

🐶Safetensors audited as really safe and becoming the default

Audit shows that safetensors is safe and ready to become the default safetensors library, the results of which allow all…

Learning Long-Term Motion Embeddings for Efficient Kinematics Generation

Learning Long-Term Motion Embeddings for Efficient Kinematics Generation AuthorsNick Stracke†‡, Kolja Bauer†‡, Stefan An…

Multivariate Probabilistic Time Series Forecasting with Informer

Multivariate Probabilistic Time Series Forecasting with Informer Introduction A few months ago we introduced the Time Se…

Image Similarity with Hugging Face Datasets and Transformers

Image Similarity with Hugging Face Datasets and Transformers We'll leverage the 🤗 datasets library as it seamlessly sup…

New and improved embedding model

The new model, text-embedding-ada-002 , replaces five separate models for text search, text similarity, and code search,…

VQ-Diffusion

VQ-Diffusion Demo 🧨 Diffusers lets you run VQ-Diffusion with just a few lines of code. Install dependencies pip install…

MTEB: Massive Text Embedding Benchmark

MTEB: Massive Text Embedding Benchmark The 🥇 leaderboard provides a holistic view of the best text embedding models out…

Automating image collection

Automating image collection Collecting images enables us to customize powerful machine learning models in new and exciti…

Building a Playlist Generator with Sentence Transformers

Building a Playlist Generator with Sentence Transformers As we’ve explored in previous posts on the Hugging Face blog, S…

Getting Started With Embeddings

Getting Started With Embeddings Understanding embeddings An embedding is a numerical representation of a piece of inform…

Generalized Visual Language Models

Processing images to generate text, such as image captioning and visual question-answering, has been studied for years. …

Graphcore and Hugging Face Launch New Lineup of IPU-Ready Transformers

Graphcore and Hugging Face Launch New Lineup of IPU-Ready Transformers Including the BERT transformer model made availab…

Hierarchical text-conditional image generation with CLIP latents

Hierarchical text-conditional image generation with CLIP latents Contrastive models like CLIP have been shown to learn r…

Introducing text and code embeddings

Introducing text and code embeddings We are introducing embeddings, a new endpoint in the OpenAI API that makes it easy …

Text and code embeddings by contrastive pre-training

Text and code embeddings by contrastive pre-training Abstract Text embeddings are useful features in many applications s…

Train a Sentence Embedding Model with 1B Training Pairs

Train a Sentence Embedding Model with 1 Billion Training Pairs We developed state-of-the-art sentence embedding models a…

Sentence Transformers in the Hugging Face Hub

Sentence Transformers in the Hugging Face Hub Sentence Transformers is a framework for sentence, paragraph and image emb…

Contrastive Representation Learning

The goal of contrastive representation learning is to learn such an embedding space in which similar sample pairs stay c…

From Autoencoder to Beta-VAE

[Updated on 2019-07-18: add a section on VQ-VAE & VQ-VAE-2.] [Updated on 2019-07-26: add a section on TD-VAE.] Autocoder…

Object Detection for Dummies Part 3: R-CNN Family

[Updated on 2018-12-20: Remove YOLO here. Part 4 will cover multiple fast object detection algorithms, including YOLO.] …

Object Detection for Dummies Part 2: CNN, DPM and Overfeat

Part 1 of the “Object Detection for Dummies” series introduced: (1) the concept of image gradient vector and how HOG alg…

Object Detection for Dummies Part 1: Gradient Vector, HOG, and SS

I’ve never worked in the field of computer vision and has no idea how the magic could work when an autonomous car is con…

Learning Word Embedding

Human vocabulary comes in free text. In order to make a machine learning model understand and process the natural langua…

Predict Stock Prices Using RNN: Part 2

In the Part 2 tutorial, I would like to continue the topic on stock price prediction and to endow the recurrent neural n…

Adversarial training methods for semi-supervised text classification

Adversarial training methods for semi-supervised text classification Abstract Adversarial training provides a means of r…

Weight normalization: A simple reparameterization to accelerate training of deep neural networks

Weight normalization: A simple reparameterization to accelerate training of deep neural networks Abstract We present wei…