{"id":17638,"date":"2023-04-10T22:15:52","date_gmt":"2023-04-10T22:15:52","guid":{"rendered":"https:\/\/www.searchenginejournal.com\/seven-free-open-source-gpt-models-released\/484195\/"},"modified":"2023-04-10T22:15:52","modified_gmt":"2023-04-10T22:15:52","slug":"seven-free-open-source-gpt-models-released-via-sejournal-martinibuster","status":"publish","type":"post","link":"https:\/\/marketingnewsbox.com\/?p=17638","title":{"rendered":"Seven Free Open Source GPT Models Released via @sejournal, @martinibuster"},"content":{"rendered":"
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Silicon Valley AI company Cerebras released seven open source GPT models to provide an alternative to the tightly controlled and proprietary systems available today.<\/p>\n

The royalty free open source GPT models, including the weights and training recipe have been released under the highly permissive Apache 2.0 license by Cerebras, a Silicon Valley based AI infrastructure for AI applications company.<\/p>\n

To a certain extent, the seven GPT models are a proof of concept for the Cerebras Andromeda AI supercomputer.<\/p>\n

The Cerebras infrastructure allows their customers, like Jasper AI Copywriter, to quickly train their own custom language models.<\/p>\n

A Cerebras blog post<\/a> about the hardware technology noted:<\/strong><\/p>\n

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\u201cWe trained all Cerebras-GPT models on a 16x CS-2 Cerebras Wafer-Scale Cluster called Andromeda.<\/p>\n

The cluster enabled all experiments to be completed quickly, without the traditional distributed systems engineering and model parallel tuning needed on GPU clusters.<\/p>\n

Most importantly, it enabled our researchers to focus on the design of the ML instead of the distributed system. We believe the capability to easily train large models is a key enabler for the broad community, so we have made the Cerebras Wafer-Scale Cluster available on the cloud through the Cerebras AI Model Studio<\/a>.\u201d<\/p>\n<\/blockquote>\n

Cerebras GPT Models and Transparency<\/h2>\n

Cerebras cites the concentration of ownership of AI technology to just a few companies as a reason for creating seven open source GPT models.<\/p>\n

OpenAI, Meta and Deepmind keep a large amount of information about their systems private and tightly controlled, which limits innovation to whatever the three corporations decide others can do with their data.<\/p>\n

Is a closed-source system best for innovation in AI? Or is open source the future?<\/p>\n

Cerebras writes:<\/strong><\/p>\n

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\u201cFor LLMs to be an open and accessible technology, we believe it\u2019s important to have access to state-of-the-art models that are open, reproducible, and royalty free for both research and commercial applications.<\/p>\n

To that end, we have trained a family of transformer models using the latest techniques and open datasets that we call Cerebras-GPT.<\/p>\n

These models are the first family of GPT models trained using the Chinchilla formula and released via the Apache 2.0 license.\u201d<\/p>\n<\/blockquote>\n

Thus these seven models are released on Hugging Face<\/a> and GitHub<\/a> to encourage more research through open access to AI technology.<\/p>\n

These models were trained with Cerebras\u2019 Andromeda AI supercomputer, a process that only took weeks to accomplish.<\/p>\n

Cerebras-GPT is fully open and transparent, unlike the latest GPT models from OpenAI (GPT-4), Deepmind and Meta OPT.<\/p>\n

OpenAI and Deepmind Chinchilla do not offer licenses to use the models. Meta OPT only offers a non-commercial license.<\/p>\n

OpenAI\u2019s GPT-4 has absolutely no transparency about their training data. Did they use Common Crawl data? Did they scrape the Internet and create their own dataset?<\/p>\n

OpenAI is keeping this information (and more) secret, which is in contrast to the Cerebras-GPT approach that is fully transparent.<\/p>\n

The following is all open and transparent:<\/strong><\/p>\n