Search Results for "clean"

LLM Datasets curates and standardizes datasets commonly used to train and fine-tune large language models, reducing the overhead of hunting down sources and normalizing formats. The repository aims to make datasets easy to inspect and transform, with scripts for downloading, deduping, cleaning, and converting to formats like JSONL that slot into training pipelines. It highlights instruction-tuning and conversation-style corpora while also pointing to code, math, or domain-specific sets for...

...This makes it easy to integrate Groq-powered AI capabilities into backend services, data pipelines, research notebooks, or applications written in Python. For those building AI-based tooling, automation scripts, or ML-backed backends, groq-python abstracts away HTTP request plumbing and exposes a clean API, accelerating development and reducing boilerplate.

...Telegram Bot API is an HTTP-based interface created for developers keen on building bots for Telegram. Complete API Methods Support. Laravel Support out of the box! Clean, Highly Documented & Industry Standard Code. PSR Standards, popular & widely used. Powered by Laravel Collection API for Response Objects. Events/Plugin Support to Extend Features Conversational Support. Well-designed, tested & built. Active support from the author as well as the community. If you're using this SDK with Laravel, the SDK will self-register its ServiceProvider and Facade using Laravel's auto-discovery. ...

...The ML-based models can be trained on potentially large datasets containing multiple time series, and some of the models offer a rich support for probabilistic forecasting. We recommend to first setup a clean Python environment for your project with at least Python 3.7 using your favorite tool (conda, venv, virtualenv with or without virtualenvwrapper).

This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2.

...Yet even the simplest addresses are packed with local conventions, abbreviations and context, making them difficult to index/query effectively with traditional full-text search engines. This library helps convert the free-form addresses that humans use into clean normalized forms suitable for machine comparison and full-text indexing. Though libpostal is not itself a full geocoder, it can be used as a preprocessing step to make any geocoding application smarter, and simpler.

CLearSharp is a clean C#-implementation of Common Lisp. The big goals are ANSI standard compliance, interoperability with Java and integration with scripting environments. This project is meant to be a sibling to CLearJ, with sharing of implementation.

CLearJ is a clean Java-implementation of Common Lisp. The big goals are ANSI standard compliance, interoperability with Java and integration with scripting environments. This project is meant to be a sibling to CLearSharp, with sharing of implementation.