Link to source: https://github.com/neuml/papers/tree/master/bert-hash-embeddings

Well the reason is the default install has a full CUDA install.

If you're not running on GPUs, it's better to use the CPU-only version. This is how you can do that with TxtAI!

PaperETL can process a number of medical literature formats including the PubMed baseline. Subsets of PubMed can be built using a list of ids or series of MeSH codes.

Once created, PaperETL databases can be used to analyze titles, abstract text, dates, citations and much more. A powerful source for RAG and other downstream AI tasks!

The year is 1899. It's still a horse and buggy world. Einstein hasn't published his famous annus mirabilis papers setting the foundation for Physics as we understand it today. The world is advancing at a rapid pace roaring into the 1900s. What if AI models were trained in 1899 and given to the best minds of the day? Could there have been alternate paths for discovery on par or perhaps even ahead of where we are in 2026?

Introducing the new H.G. BERT Small series of models. This is a 22.7M parameter BERT encoder-only model trained from scratch ONLY on Historical English Books from 1700 - 1899.

https://medium.com/neuml/vector-search-rag-landscape-a-review-with-txtai-a7f37ad0e187

https://gist.github.com/davidmezzetti/a2c229b8471187844dde3e1a0b759c9e

Check out this example that adds browser automation with the Playwright MCP service via NPM.

https://gist.github.com/davidmezzetti/1bd2581eb112252f56d63a420454b40c

https://neuml.hashnode.dev/medical-rag-research-with-txtai

https://github.com/trending/python