8 articles
Hugging Face AutoTrain enables no-code opinion classification through a web interface. Integration with Kili for data annotation. Complete workflow: labeling, training, and deploying text classification models.
Hugging Face releases a guide for using the Transformers library on Habana Gaudi accelerators. The tutorial covers installation, configuration, and optimization of deep learning models on this specialized hardware infrastructure.
Hugging Face launches an education program providing free access to models, datasets, and tools for students and educators to learn machine learning and AI.
Hugging Face releases a report on CO2 emissions from the Hub and hosted models. The article details the environmental impact of model training and deployment, with metrics and recommendations to reduce carbon footprint.
OpenAI introduces a hierarchical method for text-conditional image generation using CLIP latents. The approach improves quality and consistency between text descriptions and generated images.
OpenAI examines Goodhart's law in AI: when a metric becomes an optimization target, it ceases to be a valid measure. The challenge lies in measuring and optimizing difficult or costly objectives without degrading actual performance.
Habana Labs and Hugging Face partner to accelerate Transformer model training. The partnership aims to optimize performance on Habana's Gaudi processors and facilitate adoption by the open-source community.
Hugging Face publishes recommendations against code repetition in AI pipelines. The article promotes reusability and software architecture best practices for machine learning projects.