How NVIDIA Uses Hugging Face

The article discusses the use of NVFP4 low-precision model training to achieve higher throughput without sacrificing accuracy in AI model training.

The article discusses how NVIDIA's hardware-software co-design significantly enhanced the inference performance of Sarvam AI's Sovereign 30B model, achieving a 4x speedup on NVIDIA Blackwell archit...

The article discusses NVIDIA TensorRT LLM AutoDeploy, a beta feature that automates the inference optimization process for large language models (LLMs).

Kimi K2. 5 is an advanced multimodal vision language model (VLM) developed by Kimi, optimized for various AI tasks.

The article provides a comprehensive guide on building a document processing pipeline using NVIDIA Nemotron RAG, focusing on the extraction of structured data from complex documents like PDFs.

The article discusses how to utilize NVIDIA Earth-2 to downscale coarse climate projections into high-resolution, bias-corrected fields, enabling better assessment of local climate extremes.

This article explores how to train an AI agent to operate a new Command Line Interface (CLI) using synthetic data generation and reinforcement learning.

The article discusses the development of generalist humanoid capabilities using NVIDIA Isaac GR00T N1. 6 through a sim-to-real workflow.

The article discusses the introduction of NVIDIA TensorRT Edge-LLM, an open-source C++ framework designed for high-performance inference of Large Language Models (LLMs) and Vision Language Models (...

The article discusses the latest software and model optimizations for NVIDIA DGX Spark, highlighting significant performance improvements in AI workflows.

The article discusses the NVIDIA Rubin platform, which introduces six new chips designed to create a powerful AI supercomputer.

The article introduces NVIDIA Isaac Lab-Arena, an open-source framework designed for efficient and scalable evaluation of generalist robot policies in simulation.

This article provides a comprehensive tutorial on building a voice agent using NVIDIA's Nemotron models, focusing on retrieval-augmented generation (RAG) and safety guardrails.

The article discusses NVIDIA's Alpamayo, a comprehensive ecosystem designed for developing reasoning-based autonomous vehicle (AV) systems.

The article discusses the integration of AI Physics into Technology Computer-Aided Design (TCAD) simulations, highlighting its significance in semiconductor manufacturing.

The article discusses the NVIDIA Nemotron 3, a family of open models designed for agentic AI systems, emphasizing its efficiency and accuracy through innovative architectures and techniques.

The article discusses the creation of privacy-preserving evaluation benchmarks using synthetic data, particularly in regulated domains like healthcare.

The article discusses the implementation of Edge AI on the NVIDIA Jetson platform, focusing on the use of Large Language Models (LLMs), Vision Language Models (VLMs), and Foundation Models in robot...

The article discusses enhancing the quality of 3D Gaussian reconstruction for simulation, focusing on the use of NVIDIA's Fixer model to eliminate rendering artifacts.

The NVIDIA-accelerated Mistral 3 open model family offers developers and enterprises industry-leading accuracy, efficiency, and customization capabilities.

The article introduces Broadened Reinforcement Learning (BroRL), a new paradigm that enhances the training of large language models (LLMs) by focusing on rollout scaling rather than just increasing...

This article discusses how to achieve 4x faster inference for math problem solving using large language models by optimizing the serving stack, quantization strategy, and decoding methods.

The article discusses NVIDIA Grove, a Kubernetes API designed to streamline complex AI inference workloads by managing multicomponent systems.

The article discusses the benchmarking of AI coding assistants in writing efficient CUDA code using the ComputeEval framework.

The article discusses how NVIDIA's NeMo Automodel simplifies the training of large-scale mixture-of-experts (MoE) models in PyTorch, making it accessible to a broader audience.

The article discusses how to scale biology transformer models using PyTorch and NVIDIA BioNeMo Recipes, focusing on advanced parallel computing techniques and the integration of the NVIDIA Transfor...

The article discusses the advancements in Explainable AI for radiology through NVIDIA Clara Reason, focusing on the NV-Reason-CXR-3B model that enhances diagnostic transparency and mimics radiologi...

The article discusses how NVIDIA Run:ai enhances AI infrastructure management on Microsoft Azure by optimizing GPU utilization and simplifying workload orchestration.

The article introduces CodonFM, a new state-of-the-art RNA foundation model developed by NVIDIA as part of the Clara open model family.

The article discusses the launch of NVIDIA's new Nemotron models designed for developing specialized AI agents that integrate language and vision capabilities.

The article discusses how the NVIDIA DGX Spark supercomputer enhances performance for intensive AI tasks, providing a local alternative to cloud computing.

This article outlines a streamlined process for reconstructing 3D environments for robotics simulation using only a smartphone, specifically an iPhone.

The article discusses how to fine-tune and scale large language models (LLMs) using the open-source Unsloth framework on NVIDIA Blackwell GPUs.

This article guides readers through the process of creating a Bash computer use agent using the NVIDIA Nemotron Nano v2 model.

The article discusses building an AI agent using NVIDIA Nemotron to analyze IT tickets, focusing on extracting insights from unstructured data through advanced AI reasoning and graph databases.

The article discusses the development of an AI-powered log analysis solution using NVIDIA's Generative AI reference workflows.

The article discusses the optimization of large language models (LLMs) through pruning and knowledge distillation using NVIDIA TensorRT Model Optimizer.

The article discusses the integration of the NVIDIA KAI Scheduler with Ray, enabling advanced scheduling features like gang scheduling, workload prioritization, and autoscaling in Ray clusters.

The article discusses the integration of NVIDIA Run:ai v2. 23 with NVIDIA Dynamo to address the challenges of large language model (LLM) inference across distributed environments.

The article discusses how OpenUSD can enhance robotics development through improved data ingestion, aggregation, and the use of SimReady assets.

The article discusses the integration of computer vision pipelines with Generative AI and reasoning, highlighting the advancements in video analytics through NVIDIA's Blueprint for Video Search and...

The article provides a comprehensive guide on building a Retrieval-Augmented Generation (RAG) agent using NVIDIA Nemotron, emphasizing the integration of external information to enhance text genera...

The article introduces speculative decoding as a technique to reduce latency in AI inference, particularly for large language models (LLMs).

The article discusses the challenges of cold start latency in deploying large language models (LLMs) and introduces the NVIDIA Run:ai Model Streamer, an open-source Python SDK designed to optimize ...

This article provides a comprehensive guide on building a report generation AI agent using NVIDIA Nemotron on OpenRouter.

The article discusses the release of two new open-source models, Qwen3-Next 80B-A3B-Thinking and Qwen3-Next 80B-A3B-Instruct, which utilize a hybrid Mixture of Experts (MoE) architecture to enhance...

The article discusses how Quantization Aware Training (QAT) and Quantization Aware Distillation (QAD) can enhance low-precision model accuracy recovery beyond traditional Post-Training Quantization...

The article discusses the deployment of scalable AI inference using NVIDIA NIM Operator 3. 0. 0, highlighting its capabilities in managing AI inference pipelines across Kubernetes environments.

The article discusses how to build in-house AI systems using Outerbounds and NVIDIA DGX Cloud Lepton, emphasizing the importance of orchestrating multiple models and dynamic data.

The article discusses how to enhance the efficiency of Large Language Models (LLMs) during inference by utilizing CPU-GPU memory sharing through NVIDIA's NVLink C2C technology.