Hugging Face Jobs

Evidence (20)

• 7Hacker News·6/11/2026research
  Open reproduction of DeepSeek-R1

  Hugging Face has published open-r1, a project aimed at reproducing DeepSeek-R1 in an open-source setting. The repository and associated discussion focus on replicating the model's training and reasoning approach rather than releasing a new commercial product.

• 4Hugging Face Blog·6/9/2026framework_update
  Migrating GitHub CI to Hugging Face Jobs

  Hugging Face describes how to move continuous integration workflows from GitHub CI to Hugging Face Jobs. The post focuses on using Hugging Face's job execution system to run build, test, or automation tasks within its platform.

• 5Hugging Face Blog·6/8/2026open_source
  Open Source Community Backs OpenEnv for Agentic RL

  The Hugging Face blog reports growing open source community support for OpenEnv, a project aimed at agentic reinforcement learning. The item highlights OpenEnv as a shared infrastructure effort for building and evaluating agentic RL workflows.

• 5Hugging Face Blog·6/4/2026model_release
  Nemotron 3.5 Adds Customizable Multimodal Content Safety

  Hugging Face Blog highlights Nemotron 3.5 Content Safety, a multimodal safety system designed for enterprise AI use cases. The release focuses on customizable controls for detecting and managing unsafe content across different input types and global deployment scenarios.

• 5Hugging Face Blog·6/4/2026framework_update
  Hugging Face Designs hf CLI for Agent-Friendly Hub Workflows

  Hugging Face introduced design changes for the hf CLI to make it easier for AI agents and developers to interact with the Hub. The update focuses on more agent-optimized workflows for tasks such as managing repositories and other Hub operations from the command line.

• 5Hugging Face Blog·6/3/2026research
  Direct Preference Optimization Beyond Chatbots

  The Hugging Face blog post discusses how Direct Preference Optimization (DPO) can be applied beyond chatbot fine-tuning to a wider range of machine learning tasks. It frames DPO as a practical preference-based training approach for aligning models using human or implicit feedback without relying on more complex reinforcement learning pipelines.

• 5Hugging Face Blog·6/2/2026model_release
  Holo3.1: Fast and Local Computer Use Agents

  Hugging Face introduced Holo3.1, a computer-use agent designed to run quickly and locally. The release focuses on enabling agentic interaction with computers without relying on cloud execution, emphasizing speed and on-device deployment.

• 6Hugging Face Blog·6/1/2026model_release
  JetBrains Introduces Mellum2, a 12B MoE Model

  JetBrains has introduced Mellum2, a 12B mixture-of-experts model. The announcement positions it as a new AI model release from JetBrains, shared via the Hugging Face Blog. The post highlights the model as part of ongoing work on code-focused AI systems.

• 7Hugging Face Blog·5/27/2026framework_update
  TRL Adds Delta Weight Sync for Large-Scale Hub Bucket Training

  Hugging Face describes a new Delta Weight Sync approach in TRL that uses a Hub Bucket to ship and synchronize very large model updates more efficiently. The method is aimed at reducing the cost of moving full weights during training of extremely large models, including trillion-parameter-scale workflows.

• 3Hugging Face Blog·5/25/2026research
  Hugging Face clarifies key AI agent terms

  Hugging Face discusses the terms "harness" and "scaffold" in the context of AI agents and explains why using the right terminology matters. The post focuses on improving clarity around how agents are built, supported, and evaluated in practice.

• 7Hugging Face Blog·5/14/2026model_release
  Granite Embedding Multilingual R2 brings open multilingual embeddings with 32K context

  Hugging Face Blog highlights Granite Embedding Multilingual R2, an Apache 2.0 open multilingual embedding model designed for retrieval tasks. The release emphasizes strong retrieval quality for sub-100M parameter models and support for up to 32K context.

• 6Hugging Face Blog·5/14/2026framework_update
  Async Support for Continuous Batching

  Hugging Face introduces asynchronicity for continuous batching, aiming to improve how model requests are scheduled and processed in inference systems. The update is designed to help reduce latency and better utilize compute by allowing batching to continue without blocking on individual requests.

• 4Hugging Face Blog·5/11/2026framework_update
  AWS Building Blocks for Foundation Model Training and Inference

  The Hugging Face blog post outlines a set of building blocks for training and serving foundation models on AWS. It focuses on the infrastructure and workflow components needed to support large-scale model development and inference in a cloud environment.

• 4Hugging Face Blog·4/29/2026product_launch
  DeepInfra Joins Hugging Face Inference Providers

  Hugging Face announced that DeepInfra is now available through its Inference Providers offering. The integration expands the set of third-party model inference options available to users on the Hugging Face platform.

• 3Hugging Face Blog·4/27/2026product_launch
  How to Build Scalable Web Apps with OpenAI's Privacy Filter

  This Hugging Face Blog post explains how to use OpenAI's Privacy Filter when building scalable web applications. It focuses on applying the filter to help protect sensitive information while keeping apps performant and easier to operate at scale.

• 5Hugging Face Blog·4/16/2026research
  Ecom-RLVE: Adaptive Verifiable Environments for E-Commerce Agents

  Hugging Face introduced Ecom-RLVE, an adaptive verifiable environment designed for training and evaluating e-commerce conversational agents. The framework focuses on making agent behavior measurable and testable in realistic commerce scenarios, supporting more reliable development and benchmarking.

• 4Hugging Face Blog·4/15/2026product_launch
  HCompany Launches HoloTab, an AI Browser Companion

  HCompany has introduced HoloTab, an AI browser companion featured on the Hugging Face Blog. The product is presented as a browser-based assistant designed to help users interact with web content more efficiently. The post highlights the launch rather than detailed technical benchmarks or research results.

• 6Hugging Face Blog·4/9/2026framework_update
  Multimodal Embeddings and Rerankers in Sentence Transformers

  Hugging Face announced support for multimodal embedding and reranker models within the Sentence Transformers ecosystem. The update makes it easier to build retrieval and ranking pipelines that can handle text alongside other modalities such as images. It expands the library's usefulness for search and recommendation workflows built on open-source models.

• 8Hugging Face Blog·4/2/2026model_release
  Gemma 4 brings on-device multimodal AI to Hugging Face

  Hugging Face announced Gemma 4, a new frontier multimodal model designed to run on-device. The release highlights compact, capable AI that can process multiple input types while keeping inference local for lower latency and improved privacy.

• 6Hugging Face Blog·3/31/2026research
  mRNA Language Models Trained Across 25 Species for $165

  The article describes a low-cost experiment that trained mRNA language models across 25 species for about $165. It highlights how the work demonstrates that biologically relevant sequence modeling can be done with modest resources using modern machine learning methods.