afrideva
@afri_deva
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Joined December 2021
CPU based offline multimodal inference on an Android phone. Original model from @NousResearch, quantization done by @nisten
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@altryne How to run obsidian-multimodal. Just copy paste this in your terminal and press enter. git clone -b stablelm-support https://t.co/UFo8UzUTRt && \ cd llama.cpp && \ make && \ wget https://t.co/7NuU35C0pv && \ wget https://t.co/io5OdDRhk3 && \ ./server -m
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"We construct a dataset consisting of real Reddit profiles, and show that current LLMs can infer a wide range of personal attributes (e.g., location, income, sex), achieving up to 85% top-1 and 95.8% top-3 accuracy at a fraction of the cost (100×) and time (240×) required by
@hamandcheese @RokoMijic I think identities can be easily reverse engineered. The scary thing imo is not so much private data leaking, but correct inferences without the use of private data.
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Vector databases have raised billions offering hosted management of text embeddings. What are you revealing in these vectors ? 🔒 We demonstrate a practical method for full recovery of 90% of sentence length embeddings ( https://t.co/JNBN7mm3Wu).
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The Bitcoin whitepaper is now available in Oshiwambo (both Oshikwanyama and Oshindonga) thanks to a collaborative effort with @LandifaBitcoin and a few other Namibian Bitcoiners.
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@ceramicnetwork looks appealing for general identity with DID, with solutions for adding dynamic metadata to users/tokens
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Any recommendations for open source self-sovereign identity/authority/reputation solutions that work across EVM blockchains?
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