How to Install and Use the Hugging Face Unity API
Hugging Face released a Unity API, enabling developers to integrate Hugging Face models into Unity-based applications.
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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.
Hugging Face launched a dedicated Chinese blog and community platform to engage with Chinese AI researchers and developers.
Eugene Yan outlines 9 ML system design patterns, including human-in-the-loop, hard mining, reframing, cascade, data flywheel, and business rules layer.
Hugging Face announced optimization for Transformers on AWS Inferentia2, claiming significant performance and cost improvements for inference.
A small LLM was run on a Raspberry Pico to generate short, creative text formats like headlines and comments, demonstrating local inference.
Hugging Face blog post discusses Substra, an open-source framework for federated learning and privacy-preserving AI.
OpenAI launched a bug bounty program to incentivize researchers to discover and report security vulnerabilities in its models and platforms.
Eugene Yan details architectural design patterns for LLM planning, self-reflection, and hybrid search/recsys methods to improve RAG retrieval.
Snorkel AI and Hugging Face partnered to integrate Snorkel Flow's data labeling and programmatic workflow capabilities with Hugging Face models.
OpenAI published a blog post outlining its general approach to AI safety, focusing on responsible development and deployment.
Hugging Face released a guide and code for training LLaMA models using Reinforcement Learning from Human Feedback (RLHF).
Hugging Face published its third 'Ethics and Society' newsletter, focusing on ethical openness in AI development and deployment.
Hugging Face reported BLOOMZ model inference speedup using Habana Gaudi2 accelerators, demonstrating a potential alternative to NVIDIA GPUs.
Hugging Face and Flower collaborated on a blog post demonstrating federated learning for model training, focusing on practical implementation.
OpenAI announced initial support for plugins in ChatGPT, enabling models to access real-time information, run computations, and use third-party services.
Hugging Face and Project Jupyter announced an expanded collaboration to integrate Hugging Face tools directly within Jupyter environments.
LLMs generate biographies to assess memorization and regurgitation patterns.
OpenAI research paper assesses labor market impact potential of large language models on various occupations.
OpenAI's GPT-4 integration with Duolingo improves language tutoring and role-playing conversational experiences.
OpenAI's GPT-4 powers Be My Eyes app, offering AI-assisted visual descriptions for blind and low-vision users, expanding accessibility use cases.
Khan Academy is piloting GPT-4 to power virtual education. This is a limited program to explore potential applications.
Iceland leverages OpenAI's GPT-4 to create language models for Icelandic, addressing low-resource language preservation challenges.
Hugging Face blog post discusses using ML in a game to aid survivors, illustrating application of AI in non-traditional contexts.
Hugging Face blog post details how their platform accelerated development of Witty Works' writing assistant, likely a case study.
Hugging Face blog post discusses red-teaming methodologies for LLMs, covering adversarial attacks and safety evaluations.
Fetch, a consumer rewards app, claims 30% development time savings by consolidating AI tools on Hugging Face and AWS for internal MLOps.
Hugging Face and AWS announced a partnership focused on making AI more accessible, including optimized model deployment and training.
OpenAI published a blog post clarifying its approach to model behavior alignment, user customization, and public input in decision-making.
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