Learning with not Enough Data Part 3: Data Generation
A common problem in machine learning is having too little training data. This article discusses two approaches to generating synthetic data for traini...
A common problem in machine learning is having too little training data. This article discusses two approaches to generating synthetic data for traini...
OpenAI has developed a method for generating images based on text prompts, using the CLIP model's latent space. This approach allows for more nuanced ...
Goodhart's law states that when a measure becomes a target, it stops being a good measure. This concept, originally from economics, is relevant in AI ...
Lewis Tunstall is a machine learning expert who has worked on various projects, including the development of the Hugging Face Transformers library. He...
Habana Labs, a company specializing in AI acceleration technology, has partnered with Hugging Face, a popular platform for natural language processing...
The Hugging Face team discusses their design philosophy for the Transformers library, which aims to reduce repetition in code by providing a unified i...
Hugging Face has introduced a new type of transformer model called Decision Transformers. These models are designed to handle decision-making tasks, s...
Margaret Mitchell, a leading expert in machine learning, discusses her work and experiences. She is the founder of Hazy Research and has made signific...
The Hugging Face team has introduced a new program called the AI Research Residency, aimed at supporting early-career researchers in developing and ap...
A blog post on Hugging Face's website explains how to fine-tune a pre-trained segmentation model, SegFormer, using a custom dataset. The process invol...
Hugging Face, a popular open-source library for natural language processing (NLP), has partnered with Amazon Web Services (AWS) to accelerate the infe...
Researchers have created a collection of image datasets, called π€ datasets, which can be used for various computer vision tasks. The datasets include ...