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Hugging Face, Inc. is an American company incorporated under the Delaware General Corporation Law [1] and based in New York City that develops computation tools for building applications using machine learning.
The plain transformer architecture had difficulty converging. In the original paper [1] the authors recommended using learning rate warmup. That is, the learning rate should linearly scale up from 0 to maximal value for the first part of the training (usually recommended to be 2% of the total number of training steps), before decaying again.
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
Hugging Face, of course, is the world’s leading repository for open-source AI models—the GitHub of AI, if you will. ... it is simple to create prompts—some of which might seem like gibberish ...
The cloud computing arm of Alphabet Inc said on Thursday it had formed a partnership with startup Hugging Face to ease artificial intelligence (AI) software development in the company's Google Cloud.
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
In November 2024, an API key for Sora access was leaked by a group of testers on Hugging Face, who posted a manifesto stating they protesting that Sora was used for "art washing". OpenAI revoked the access three hours after the leak was made public, and gave a statement that "hundreds of artists" have shaped the development, and that ...
This is because deep learning models are able to learn the style of an artist or musician from huge datasets and generate completely new artworks and music compositions. For instance, DALL-E is a deep neural network trained on 650 million pairs of images and texts across the internet that can create artworks based on text entered by the user. [246]