Search Results for "as/400"

n8n is an extendable workflow automation tool. With a fair-code distribution model, n8n will always have visible source code, be available to self-host, and allow you to add your own custom functions, logic and apps. n8n's node-based approach makes it highly versatile, enabling you to connect anything to everything. n8n has 200+ different nodes to automate workflows.

TokenCost is an open-source developer utility designed to estimate the cost of using large language model APIs by calculating token usage and translating it into real monetary values. The tool focuses on helping developers understand how much their prompts and generated completions cost when interacting with commercial AI models. It works by counting tokens in prompts and responses before or after sending requests and then applying pricing information associated with different models. This...

Enlightened library to convert HTML and CSS to SVG. Satori supports the JSX syntax, which makes it very straightforward to use. Satori will render the element into a 600×400 SVG, and return the SVG string. Under the hood, it handles layout calculation, font, typography and more, to generate a SVG that matches the exact same HTML and CSS in a browser. Satori only accepts JSX elements that are pure and stateless. You can use a subset of HTML elements (see section below), or custom React components, but React APIs such as useState, useEffect, dangerouslySetInnerHTML are not supported. ...

...The original version of CLIPS Rule Based Programming Language is available from here. https://sourceforge.net/p/clipsrules/ The misclns4.tst is a good example for it because HyperCLIPS performs 200% - 400% faster than the original version of CLIPS. The CLIPS test suite(including misclns4.tst) are available from here. https://sourceforge.net/p/clipsrules/code/HEAD/tree/branches/63x/test_suite

GLM-130B is an open bilingual (English and Chinese) dense language model with 130 billion parameters, released by the Tsinghua KEG Lab and collaborators as part of the General Language Model (GLM) series. It is designed for large-scale inference and supports both left-to-right generation and blank filling, making it versatile across NLP tasks. Trained on over 400 billion tokens (200B English, 200B Chinese), it achieves performance surpassing GPT-3 175B, OPT-175B, and BLOOM-176B on multiple benchmarks, while also showing significant improvements on Chinese datasets compared to other large models. The model supports efficient inference via INT8 and INT4 quantization, reducing hardware requirements from 8× A100 GPUs to as little as a single server with 4× RTX 3090s. ...

What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning. From theory to the actual code that you can directly put into action! This is not yet just another "this is how scikit-learn works" book. I aim to explain all the underlying concepts, tell you everything you need to know in terms of best practices and caveats, and we will put those concepts into action mainly using NumPy, scikit-learn, and Theano. ...