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PCPartPicker TABLUM.IOPCPartPicker is recommended for anyone interested in building their own computer. It's especially useful for individuals who want to ensure component compatibility, compare prices, and seek advice or inspiration from a community of like-minded tech enthusiasts.
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Based on our record, PCPartPicker seems to be a lot more popular than TABLUM.IO. While we know about 4768 links to PCPartPicker, we've tracked only 3 mentions of TABLUM.IO. 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.
The RTX market is particularly irritating right now, even second-hard 4090s are still going for MSRP if you can find them at all. Most of the recommendations for this budget AI system are on point - the only thing I'd recommend is more RAM. 32GB is not a lot - particularly if you start to load larger models through formats such as GGUF and want to take advantage of system ram to split the layers at the cost of... - Source: Hacker News / 4 months ago
Cool. What about giving the models for a given GPU? Also it could compare using vLLM, local_llama.c, etc. Links to docs maybe. People could upload their builds and rate their experience. Along the lines of https://pcpartpicker.com/ And you can definitely add some ref links for a bit of revenue. - Source: Hacker News / 7 months ago
Usually I just use PCPartPicker https://pcpartpicker.com/. - Source: Hacker News / over 1 year ago
Before looking for a book like this, have you considered if you really need one? There are tons of configuratros for PCs these days (example, which I am using: https://pcpartpicker.com). I built 2x PCs already with it. Saves lots of time and you don't need to know everything to use it. - Source: Hacker News / over 1 year ago
| Generated by [PCPartPicker](https://pcpartpicker.com) 2023-12-11 21:37 EET+0200 |. Source: almost 2 years ago
For the data loaded from the raw and unstructured data sources (RESTful APIs, files, feeds) I'd recommend checking tablum.io. The data first gets into the staging SQL DB where you can apply transformations in SQL (ClickHouse dialect with hundreds of ready-to-use functions for aggregations, transformations, string and array processing, etc). After that, you can set up a pipeline to external DWH or DB. Or just... Source: over 2 years ago
Fairly easy to parse it with Python (or any other scripting languages that support regular expressions). Besides, there're no-code parsers that can do that. E.g. tablum.io, it has a regexp parser that turns poorly formatted text into an SQL table. All you need it is to provide the regular expression (regexp) to split the text (per-line basis or the entire text) into chunks that become SQL rows and columns, after... Source: over 2 years ago
You're right. There should be some way to safely pass the authentication token without storing it in the query. BTW, to keep all data within the company network perimeter and no share any keys with the cloud service, one can install tablum.io as a self-hosted version on a Linux server (it runs in Docker). Source: over 2 years ago
Logical Increments - Logical Increments is a website designed for the gamers only.
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