Hugging Face Hub on the AWS Marketplace: Pay with your AWS Account
Hugging Face Hub services are now available on AWS Marketplace, allowing enterprises to pay through existing AWS accounts.
Hugging Face Blog·10 Aug
Search signals, briefings, company results, benchmarks and glossary terms.
Search signals, briefings, company results, benchmarks and glossary terms.
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Hugging Face Hub services are now available on AWS Marketplace, allowing enterprises to pay through existing AWS accounts.
Hugging Face blog post demonstrates deploying DeepFloyd IF with BentoML for local inference, highlighting open-source model operationalization.
Hugging Face published a tutorial on fine-tuning Llama 2 using Direct Preference Optimization (DPO) for improved alignment.
Hugging Face researchers published a blog post outlining the potential for Fully Homomorphic Encryption (FHE) to secure LLM inference.
Hugging Face is using ML models to automatically identify and tag the specific language (e.g., 'English (US)') of datasets and models on its Hub.
OpenAI hosted a workshop on AI confidence-building measures, discussing safety, security, and responsible development frameworks with diverse stakeholders.
Eugene Yan outlines common architectural patterns for LLM systems, including RAG, fine-tuning, caching, guardrails, and defensive UX.
OpenAI, Anthropic, Google, and Microsoft formed the Frontier Model Forum to advance safe and responsible frontier AI development.
Hugging Face published an analysis of the EU AI Act's implications for open-source AI, focusing on potential compliance burdens.
OpenAI and other frontier AI labs commit to voluntary safety, security, and trustworthiness measures in AI development and deployment.
Hugging Face hosted an Open Source AI Game Jam, showcasing novel applications of open-source AI models in game development.
OpenAI partners with the American Journalism Project with a $5M+ investment to explore AI's role in local news and ensure news organizations shape its future.
Meta released Llama 2, an open-source large language model, available on Hugging Face, enabling broader access and fine-tuning capabilities.
Hugging Face is a key player in the open-source LLM ecosystem, providing models, datasets, and tools for text generation.
Hugging Face demonstrates fine-tuning Stable Diffusion models on Intel CPUs, leveraging specific optimizations for faster training.
Viable claims to use GPT-4 for analyzing large-scale qualitative data with high accuracy, suggesting new application patterns.
OpenAI published 'Frontier AI regulation: Managing emerging risks to public safety,' outlining their stance on proactive AI governance.
Hugging Face offers managed inference endpoints for deploying open-source LLMs, providing scaling and security features for enterprise users.
Hugging Face published a blog post discussing leveraging their platform for complex generative AI use cases.
Hugging Face demonstrated BridgeTower vision-language model inference optimization on Habana Gaudi2 hardware for improved performance.
OpenAI announced the opening of its first international office in London, United Kingdom, to focus on AI research and development.
Hugging Face's Open LLM Leaderboard faced integrity concerns, prompting a temporary freeze and an investigation into benchmark gaming.
Hugging Face hosted an enterprise AI panel discussing challenges and opportunities for integrating open-source models in large organizations.
OpenAI CEO Sam Altman testified before the U.S. Senate, emphasizing the need for AI regulation, including licensing and safety standards.
Hugging Face submitted comments to U.S. NTIA on AI accountability, advocating for open-source AI and transparent risk management frameworks.
Hugging Face now supports deploying Elixir-based Livebook notebooks as interactive web applications directly to Hugging Face Spaces.
Hugging Face and AMD partnered to optimize AI models for AMD's CPU and GPU platforms, aiming to improve performance and accessibility.
Hugging Face is promoting its platform for Galleries, Libraries, Archives, and Museums (GLAM) to host and collaborate on AI models and datasets.
Hugging Face research explores foundation models' ability to label data compared to human annotators, impacting data pipeline efficiency.
OpenAI provided comments to NTIA on AI accountability policies, advocating for flexible, risk-based frameworks over prescriptive regulation.
Eugene Yan details Obsidian-Copilot, an RAG-based personal AI assistant for writing and reflection from personal journal entries.
Chip Huyen presented a framework for developing a generative AI strategy, addressing common enterprise challenges in adoption.
Hugging Face announced integration of DuckDB, enabling direct SQL analysis on 50,000+ datasets hosted on the Hugging Face Hub.
Hugging Face integrated fastText into its Hub, enabling easier access and sharing of fastText models and embeddings for text classification and representation.
TII's Falcon LLM series is now available on Hugging Face, including optimized versions and integration with the Hugging Face ecosystem.
Hugging Face detailed integrating AI speech recognition models with Unity game engine, enabling real-time voice interaction.
OpenAI launched a grant program to fund AI-powered cybersecurity tools for defenders, focusing on open-source and public goods.
Hugging Face is hosting an Open Source AI Game Jam, encouraging developers to build games using open-source AI models and tools.
Hugging Face now natively integrates BERTopic, an open-source topic modeling framework, making it easier for users to deploy and share topic models.
Hugging Face released an LLM Inference Container for AWS SageMaker, simplifying model deployment and management for enterprises.
OpenAI's non-profit, OpenAI, Inc., launched a grant program offering ten $100,000 awards to fund experiments on democratic AI rule-setting processes.
Hugging Face is integrating its Model Catalog directly into Microsoft Azure, making open-source models more accessible for Azure users.
Hugging Face and IBM announced a partnership to integrate Hugging Face models and open-source capabilities into IBM's watsonx.ai platform.
Intel claims Q8-Chat, an 8-bit quantized LLM, runs efficiently on Xeon, potentially lowering local inference costs.
Hugging Face was selected by France's CNIL for its enhanced support program, indicating increased regulatory engagement with open-source AI platforms.
OpenAI used GPT-4 to generate and score explanations for individual neuron behavior in GPT-2, releasing a dataset of these explanations.
Hugging Face released StarCoder, an open-source LLM specifically for code generation, finetuned on a large dataset of GitHub code.
Hugging Face released a Unity API, enabling developers to integrate Hugging Face models into Unity-based applications.
Hugging Face detailed how to train language models using its Transformers library with TensorFlow on Google's TPUs.
Databricks announced a collaboration with Hugging Face to optimize LLM training and tuning, claiming up to 40% speed improvements.
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