New Week Brings Local Run Capability for LLMs with Added OpenAI Privacy Filter Model
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| Source: Mastodon | Original article
New AI model added for local LLM use. OpenAI's Privacy-Filter model is now available.
New developments in running Large Language Models (LLMs) locally have emerged, with the addition of OpenAI's Privacy-Filter model. This model, which can be used to filter out sensitive information, has been incorporated using the privacy-filter.cpp tool. The update is part of a broader effort to enable local execution of LLMs, allowing for more secure and private data processing.
This matters because running LLMs locally reduces the risk of exposing sensitive data, as it does not require sending data to a server for processing. OpenAI's Privacy-Filter model is particularly noteworthy, as it is designed to detect and redact personally identifiable information (PII) while being small enough to run on a local device.
As the field of LLMs continues to evolve, it will be important to watch how these local models are adopted and integrated into various applications. The Hugging Face community, for example, is already exploring the use of local LLMs, with new slides available on the economics and hardware used by the community. Further developments in this area are likely to have significant implications for data privacy and security.
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