AI 뉴스

OpenAI Scholars 2021: Final projects

We’re proud to announce that the 2021 class of OpenAI Scholars has completed our six-month mentorship program and have produced an open-source research project with stipends and support from OpenAI.

Will Hurd joins OpenAI’s board of directors

OpenAI is committed to developing general-purpose artificial intelligence that benefits all humanity, and we believe that achieving our goal requires expertise in public policy as well as technology. So, we’re delighted to announce that Congressman Will Hurd has joined our board of directors.

Scaling-up BERT Inference on CPU (Part 1)

Introducing 🤗 Accelerate

Distributed Training: Train BART/T5 for Summarization using 🤗 Transformers and Amazon SageMaker

Understanding BigBird's Block Sparse Attention

GPT-3 powers the next generation of apps

Over 300 applications are delivering GPT-3–powered search, conversation, text completion, and other advanced AI features through our API.

The Partnership: Amazon SageMaker and Hugging Face

My Journey to a serverless transformers pipeline on Google Cloud

Fine-Tune Wav2Vec2 for English ASR in Hugging Face with 🤗 Transformers

Hugging Face Reads, Feb. 2021 - Long-range Transformers

Multimodal neurons in artificial neural networks

We’ve discovered neurons in CLIP that respond to the same concept whether presented literally, symbolically, or conceptually. This may explain CLIP’s accuracy in classifying surprising visual renditions of concepts, and is also an important step toward understanding the associations and biases that…

Simple considerations for simple people building fancy neural networks

Retrieval Augmented Generation with Huggingface Transformers and Ray

Hugging Face on PyTorch / XLA TPUs

Understanding the capabilities, limitations, and societal impact of large language models

Faster TensorFlow models in Hugging Face Transformers

Scaling Kubernetes to 7,500 nodes

We’ve scaled Kubernetes clusters to 7,500 nodes, producing a scalable infrastructure for large models like GPT-3, CLIP, and DALL·E, but also for rapid small-scale iterative research such as Scaling Laws for Neural Language Models.

Fit More and Train Faster With ZeRO via DeepSpeed and FairScale

How we sped up transformer inference 100x for 🤗 API customers