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CPU based offline multimodal inference on an Android phone. Original model from @NousResearch, quantization done by @nisten
@altryne How to run obsidian-multimodal.
Just copy paste this in your terminal and press enter.
git clone -b stablelm-support github.com/Galunid/llama.cpp… && \
cd llama.cpp && \
make && \
wget huggingface.co/nisten/obsidi… && \
wget huggingface.co/nisten/obsidi… && \
./server -m obsidian-q6.gguf --mmproj mmproj-obsidian-f16.gguf -ngl 42
afrideva retweeted
"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 humans." arxiv.org/abs/2310.07298v1
afrideva retweeted
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 (arxiv.org/abs/2310.06816).
afrideva retweeted
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.
Any recommendations for open source self-sovereign identity/authority/reputation solutions that work across EVM blockchains?
@ceramicnetwork looks appealing for general identity with DID, with solutions for adding dynamic metadata to users/tokens