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Contrastive Language-Image Pre-training (CLIP) is a technique for training a pair of neural network models, one for image understanding and one for text understanding, using a contrastive objective. [1]
Hugging Face, Inc. is an American company that develops computation tools for building applications using machine learning. It is known for its transformers library ...
An output of pip install virtualenv. Pip's command-line interface allows the install of Python software packages by issuing a command: pip install some-package-name. Users can also remove the package by issuing a command: pip uninstall some-package-name. pip has a feature to manage full lists of packages and corresponding version numbers ...
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.
Their rationale is to allow users to manage the software dependency on data, such as machine learning models for data-driven applications. They are useful to publish, locate, and install data packages. A typical example of a data dependency management frameworks are Hugging Face, KBox, [31] among others.
BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [3]
From January 2008 to December 2012, if you bought shares in companies when Thomas P. Mac Mahon joined the board, and sold them when he left, you would have a 48.8 percent return on your investment, compared to a -2.8 percent return from the S&P 500.
Meta (formerly known as Facebook) operates both PyTorch and Convolutional Architecture for Fast Feature Embedding , but models defined by the two frameworks were mutually incompatible. The Open Neural Network Exchange ( ONNX ) project was created by Meta and Microsoft in September 2017 for converting models between frameworks.