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Based on our record, FuzzyWuzzy should be more popular than BaseTen. It has been mentiond 11 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I’ve been using baseten (https://baseten.co) and it’s been fun and has reasonable prices. Sometimes you can run some of these models from the hugging face model page, but it’s hit or miss. - Source: Hacker News / 5 months ago
Thanks! Vllm for quick set up, TRT-LLM for best performance. Both available on https://baseten.co/. - Source: Hacker News / 6 months ago
Truss, first developed at Baseten, is an open source project under the MIT license. We have committed to long-term support and development for Truss — it is deeply integrated in our product strategy — but it lives as an independent project that emphasizes compatibility and interoperability. Source: almost 2 years ago
Baseten | REMOTE (US, Canada, Europe, and more), SF US | Full-time | https://baseten.co A personal note: I joined Baseten just over a month ago after seeing a post in January's "Who is Hiring" on HN, and I am very happy here. Baseten is an IaaS for data scientist teams that wants to build apps out of their AI models. We have customers like Patreon and Pipe, are well-funded, and are carefully expanding our team.... - Source: Hacker News / about 2 years ago
Baseten | Remote (US, Canada, Europe, and more), SF US | Full-time | https://baseten.co Baseten is an IaaS for data scientist teams that wants to build apps out of their AI models. We've got multiple clients, a successful series A and are carefully expanding our team. We're still under 15, and fly over to SF around once every 3 months. If python, typescript, lots of kubernetes tools, and a really diverse team from... - Source: Hacker News / over 2 years ago
Do fuzzy matching (something like fuzzywuzzy maybe) to see if the the words line up (allowing for wrong words). You'll need to work out how to use scoring to work out how well aligned the two lists are. Source: over 1 year ago
Convert the original lines to full furigana and do a fuzzy match. (For reference, the original line is 貴方がこれまでに得てきた力、存分に発揮してくださいね。) You can do a regional search using the initial scene data (E60) first, and if the confidence is low, go for a slower full search. Source: over 1 year ago
It's now known as "thefuzz", see https://github.com/seatgeek/fuzzywuzzy. Source: almost 2 years ago
You can have a look at this library to use fuzzy search instead of looking for plaintext muck: https://github.com/seatgeek/fuzzywuzzy. Source: over 2 years ago
To deal with comparing the string, I found FuzzyWuzzy ratio function that is returning a score of how much the strings are similar from 0-100. Source: almost 3 years ago
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