Knowledge catalogue
This article explores profiling techniques for attention mechanisms in PyTorch, the computational bottleneck in transformer models. It likely provides practical tools and methods for measuring and ana
This resource discusses open datasets and data resources designed to support the development and training of AI agents, likely covering data collection methodologies, benchmark datasets, and best prac
This entry covers the integration of vLLM, a high-performance inference engine, with Hugging Face's transformers library to enable faster language model inference. The native-speed backend allows user
This article describes Hugging Face's integration with Amazon SageMaker Studio that enables users to deploy models directly from the Hugging Face Model Hub to SageMaker with a single click, streamlini
This article describes how to use Hugging Face models with Microsoft's Foundry Managed Compute infrastructure, likely covering integration steps, deployment options, and the benefits of running open-s
LeRobot v0.6.0 is a release from Hugging Face that introduces new capabilities for robotic learning, likely including features for imagining/generating robot behaviors, evaluating model performance, a
SkyPilot enables users to run AI workloads across multiple cloud providers while storing data on Hugging Face with zero egress costs, eliminating expensive data transfer fees. This integration allows
Hugging Face announced major updates to their Kernels platform, which is their cloud-based computational environment for machine learning and data science projects. The revamp likely includes improvem
This article discusses Photoroom's data strategy for their PRX project, likely covering approaches to data collection, curation, and management used in developing their AI models or systems. The piece
Hugging Face and Cerebras have collaborated to integrate Google's Gemma 4 model with real-time voice AI capabilities, enabling faster speech processing and voice interactions. This integration likely
Hugging Face introduced a feature that displays evaluation results from the 'Every Eval Ever' (EEE) community evaluation initiative directly on model pages, providing users with comprehensive benchmar
ScarfBench is a benchmarking framework designed to evaluate AI agents' capabilities in migrating enterprise Java applications to modern frameworks. The benchmark likely assesses how well AI systems ca
This article discusses why specialization in AI models and systems is becoming an inevitable trend, likely examining factors such as the limitations of generalist approaches, efficiency gains from foc
DiScoFormer is a unified transformer architecture designed to handle both density estimation and score-based modeling across different probability distributions. The model enables a single framework t
This guide demonstrates how to deploy a vLLM (a fast, open-source LLM serving engine) server on Hugging Face Jobs using a single command, streamlining the process of setting up and running an inferenc
This article from Allen AI discusses how hybrid models that combine different prediction approaches perform across various token types, likely comparing their effectiveness on common tokens versus rar
NVIDIA NeMo AutoModel is a tool designed to accelerate the fine-tuning process of transformer models by automating model selection and configuration. The solution leverages NVIDIA's NeMo framework to
The FFASR Leaderboard is a benchmarking platform introduced by Hugging Face for evaluating Automatic Speech Recognition (ASR) systems on real-world performance metrics. It provides a standardized eval
CUGA is a lightweight framework from IBM Research for building agentic AI applications, featuring two dozen practical working examples. The framework enables developers to create autonomous AI agents
This article explores the Cross-Origin Storage API and its implementation within Transformers.js, a JavaScript library for machine learning models. It likely discusses how this API enables secure cros
This article describes Hugging Face's automated weekly release process for the huggingface_hub library, which combines AI-assisted tools with human oversight to streamline software deployment. The app
PP-OCRv6 is a multilingual optical character recognition (OCR) model family released by PaddlePaddle that supports 50 languages across multiple parameter sizes ranging from 1.5M to 34.5M. The model se
This article discusses using local language models to automatically triage pull requests in the OpenClaw repository at no cost, eliminating the need for expensive API-based solutions. The post likely
This paper benchmarks frontier automatic speech recognition (ASR) systems on their ability to handle code-switched speech, where bilingual speakers mix languages within a single conversation. The rese
This article describes how an AI agent was used to create a 3D virtual gallery of Paris by chaining together two Hugging Face Spaces applications. It demonstrates a practical example of using agents t
Cohere Labs introduced North Mini Code, a compact code generation model designed specifically for developers, marking Cohere's entry into specialized coding models. The model is optimized for efficien
This article explains how to migrate continuous integration workflows from GitHub Actions to Hugging Face Jobs, likely covering the setup process, configuration differences, and benefits of using Hugg
Building Pakistan Notice Helper is a small AI tool designed to address a localized safety issue in Pakistan by helping users understand and process building-related notices. Developed as a hackathon p
OpenEnv is an open-source framework backed by the community for training and developing agentic reinforcement learning systems. The project represents collaborative efforts within the open-source ecos
Amazing Digital Dentures was a hackathon project showcased on Hugging Face that attempted to apply AI or digital technology to denture design or manufacturing but ultimately did not reach completion o
This resource describes sponsor vouchers, particularly OpenAI Codex credits, available to participants in a Hugging Face hackathon event. It likely outlines how participants can access and use the pro
This article describes a collaborative hackathon project involving five research labs that developed a financial simulation drama using small language models, focusing on building complex multi-agent
Job Searcher is a project showcased in a Hugging Face hackathon blog post that demonstrates how to build a job search application, likely leveraging machine learning and Hugging Face tools to help use
Thousand Token Wood is a multi-agent economy simulation built on a 3 billion parameter language model, demonstrating how small models can power complex interactive systems with multiple agents. The pr
The Hugging Face CLI (command-line interface) is designed as an agent-optimized tool that enables AI agents and users to interact with the Hugging Face Hub more efficiently. The design prioritizes com
EVA-Bench Data 2.0 is an expanded benchmark dataset containing tools and scenarios across 3 domains, featuring 121 tools and 213 test scenarios for evaluating AI agent performance. This dataset enable
This guide explains how to adapt NVIDIA's Nemotron 3.5 Automatic Speech Recognition (ASR) model to specific languages, domains, or accents through fine-tuning techniques. It likely covers the fine-tun
Nemotron 3.5 Content Safety is NVIDIA's multimodal safety solution designed for enterprise AI applications, offering customizable safeguards for both text and image inputs across different global cont
This article describes how to integrate Model Context Protocol (MCP) tools with Reachy Mini, a small humanoid robot platform. It likely covers the technical steps for extending Reachy Mini's capabilit
Direct Preference Optimization (DPO) is a fine-tuning technique that aligns language models with human preferences by directly optimizing for preferred outputs over dispreferred ones, offering an alte
Holo3.1 is a computer use agent developed by Hugging Face that enables fast, local execution of tasks on computing systems without requiring cloud infrastructure. The model is designed to interpret an
Enterprise AI adoption at scale requires moving beyond large language models to implement agent logic systems that can handle complex reasoning, planning, and decision-making autonomously. Agent-based
Mellum2 is a 12-billion parameter Mixture-of-Experts language model developed by JetBrains, designed to efficiently process complex tasks by selectively activating different expert networks. The model
NVIDIA Cosmos 3 is an open-source omni-model designed for physical AI reasoning and action tasks, representing an advancement in multimodal AI systems. The model integrates multiple modalities to enab
This guide introduces torch.profiler, PyTorch's built-in profiling tool for analyzing model performance and identifying computational bottlenecks. It covers the basics of using the profiler to measure
ITBench-AA is a new benchmark developed by Artificial Analysis and IBM that evaluates frontier AI models on agentic enterprise IT tasks, with results showing that current leading models score below 50
Reachy Mini, a robotic system, can now operate with fully local processing capabilities, enabling on-device inference without requiring cloud connectivity. This advancement allows the robot to run AI
Delta Weight Sync (DWS) is a technique for efficiently distributing and synchronizing large language models with trillions of parameters across distributed systems using Hugging Face's TRL (Transforme
This article defines and clarifies key terminology related to AI agents, including the concepts of 'harness' and 'scaffold,' which are important architectural and operational components in building an
Nemotron-Labs Diffusion Language Models represent NVIDIA's approach to achieving faster text generation through diffusion-based architectures, potentially offering significant speed improvements over
This article argues that specialized AI models often outperform larger, general-purpose models for specific use cases, challenging the common procurement assumption that bigger is always better. It li
The Ettin Reranker Family represents a new suite of reranking models released on Hugging Face designed to improve retrieval-augmented generation (RAG) systems by reordering search results based on rel
OlmoEarth v1.1 represents an updated release of Allen AI's open-source language models designed with improved efficiency compared to the original version. The update likely focuses on reduced computat
This guide demonstrates how to fine-tune NVIDIA's Cosmos Predict 2.5 video generation model using parameter-efficient techniques like LoRA (Low-Rank Adaptation) and DoRA (Mixture of Experts-based adap
PaddleOCR 3.5 introduces a Transformers-based backend for optical character recognition (OCR) and document parsing tasks, enabling improved performance and integration with the Hugging Face ecosystem.
The Open Agent Leaderboard is a benchmarking system hosted on Hugging Face that evaluates and ranks AI agents based on their performance across various tasks and capabilities. It provides a standardiz
Granite Embedding Multilingual R2 is an open-source multilingual embedding model released by IBM under the Apache 2.0 license, featuring a 32K context window and sub-100M parameters. The model is opti
This article explains how asynchronous processing can be integrated with continuous batching techniques to improve inference efficiency in machine learning models. Continuous batching allows requests
This article discusses AWS infrastructure, tools, and services designed to support the training and deployment of large foundation models, enabling machine learning practitioners to leverage AWS's com
MachinaCheck is a multi-agent AI system designed to assess the manufacturability of parts for CNC (Computer Numerical Control) machining, built on AMD's MI300X GPU architecture. The system likely leve