MindsDB
hyperfine
MindsDB | hyperfine | |
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78 | 74 | |
21,312 | 20,020 | |
1.5% | - | |
10.0 | 8.1 | |
6 days ago | 4 days ago | |
Python | Rust | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
MindsDB
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What’s the Difference Between Fine-tuning, Retraining, and RAG?
Check us out on GitHub.
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How to Forecast Air Temperatures with AI + IoT Sensor Data
If your data lacks uniform time intervals between consecutive entries, QuestDB offers a solution by allowing you to sample your data. After that, MindsDB facilitates creating, training, and deploying your time-series models.
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Fine-tuning a Mistral Language Model with Anyscale
MindsDB is an open-source AI platform for developers that connects AI/ML models with real-time data. It provides tools and automation to easily build and maintain personalized AI solutions.
- Vanna.ai: Chat with your SQL database
- FLaNK Weekly 08 Jan 2024
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MindsDB Docker Extension: Build ML powered apps at a much faster pace
MindsDB combines both AI and SQL functions in one; users can create, train, optimize, and deploy ML models without the need for external tools. Data analysts can create and visualize forecasts without having to navigate the complexities of ML pipelines.MindsDB is open-source and works with well-known databases like MySQL, Postgres, Redit, Snowflakes, etc.
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How Modern SQL Databases Are Changing Web Development - #4 Into the AI Era
Mindsdb is a good example. It abstracts everything related to an AI workflow as "virtual tables". For example, you can import OpenAI API as a "virtual table":
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🐍🐍 23 issues to grow yourself as an exceptional open-source Python expert 🧑💻 🥇
Repo : https://github.com/mindsdb/mindsdb
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AI-Powered Selection of Asset Management Companies using MindsDB and LlamaIndex
MindsDB is an AI Automation platform for building AI/ML powered features and applications. It works by connecting any data source with any AI/ML model or framework and automating how real-time data flows between them. MindsDB is integrated with LlamaIndex, which makes use of its data framework for connecting custom data sources to large language models. LlamaIndex data ingestion allows you to connect to data sources like PDF’s, webpages, etc., provides data indexing and a query interface that takes input prompts from your data and provides knowledge-augmented responses, thus making it easy to Q&A over documents and webpages.
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Using Large Language Models inside your database with MindsDB
Now, imagine if you can deploy these highly trained models in your database to get insights, make predictions, understand your users, auto-generate content, and more. MindsDB makes this possible! MindsDB is an open-source AI database middleware that allows you to supercharge your databases by integrating various machine learning (ML) engines.
hyperfine
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Measuring startup and shutdown overhead of several code interpreters
Check out the official hyperfine Github repo
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Bun - The One Tool for All Your JavaScript/Typescript Project's Needs?
And then I used hyperfine to run the benchmarks on my MacBook Pro 14 M2 Max, and here are the results:
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Faster tetranucleotide (k-mer) frequencies!
Search "benchmarking tools for linux" and decide that hyperfine is good for what I'm doing. Run Jennifer's new python script against my refactored perl and find that the python is 1.26 times faster for k=3 and 1.47 times faster for k=4. For the Covid-19 sequence, these are both on the order of hundreds of milliseconds.
- Hyperfine: A command-line benchmarking tool
- FLaNK Weekly 08 Jan 2024
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Show HN: Inshellisense – IDE style shell autocomplete
> It is very possible to write sub 100ms procedures in TS, […]
I will not disagree with this statement because I don’t have a way to test inshellisense right now. Could you (or anyone with a working Node + NPM installation) please install inshellisense and post the actual numbers? Perhaps using a tool like hyperfine (https://github.com/sharkdp/hyperfine).
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Firefox has surpassed Chrome on Speedometer
Yeah, while it's not as thorough as these tools, the method is at least reproducible and sane, and with ~10 or so samples, you get an interval with a nice confidence.
Another through method will be hyperfine[0], yet I wanted to provide a method which requires no installation and can be done in a whim, without jumps and hoops, with the tools already at hand.
[0]: https://github.com/sharkdp/hyperfine
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How to optimize your config? What are mistakes to avoid when optimizing your config?
That is native and inbuild but I would suggest below options instead 1. Using lazy's Profile tab instead https://github.com/folke/lazy.nvim 2. Using a dedicated plugin to do this https://github.com/dstein64/vim-startuptime. 3. Using an external program hyperfine is one that I use https://github.com/sharkdp/hyperfine
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How to remove all <br> from all of my .html files
Fair enough, although might I recommend using hyperfine for your testing? ;p
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
criterion.rs - Statistics-driven benchmarking library for Rust
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
fd - A simple, fast and user-friendly alternative to 'find'
postgresml - The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.
ripgrep - ripgrep recursively searches directories for a regex pattern while respecting your gitignore
CapRover - Scalable PaaS (automated Docker+nginx) - aka Heroku on Steroids
awesome-mac - Now we have become very big, Different from the original idea. Collect premium software in various categories.
scikit-learn - scikit-learn: machine learning in Python
kubeconform - A FAST Kubernetes manifests validator, with support for Custom Resources!
lightwood - Lightwood is Legos for Machine Learning.
quinn - Async-friendly QUIC implementation in Rust