Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.
API method:
GET /api/packages?search=hello&page=1&limit=20
where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned
in response headers.
If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.
Nimf is a lightweight, fast and extensible input method framework. This package provides a fork of the original nimf project, that focuses especially on Korean input (Hangul, Hanja, ...).
This module provides a utility method, "to_identifier" for converting an arbitrary string into a readable representation using the ASCII subset of "\w" for use as an identifier in a computer program. The intent is to make unique identifier names from which the content of the original string can be easily inferred by a human just by reading the identifier.
This is an official neural network of a ``main run'' of the Leela Chess Zero project. The network was finished being trained in September of 2023.
Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.
Leela Chess Zero is a UCI-compliant chess engine designed to play chess using neural networks. This package does not provide a neural network, which is necessary to use Leela Chess Zero and should be installed separately.
Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.
This is a smaller version of the T1 neural network, which is currently one of the best neural networks for Leela Chess Zero.
T1 is currently one of the best neural networks for Leela Chess Zero, however, it was superseded by the neural network T2.
This is an official neural network of the Leela Chess Zero project that was finished being trained in April of 2022.
T2 is currently one of the best neural networks for Leela Chess Zero, superseding the neural network T1.
Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.
Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.
Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.
This is an official neural network of a ``main run'' of the Leela Chess Zero project that was finished being trained in January of 2022.
This is a smaller version of the T1 neural network, which is currently one of the best neural networks for Leela Chess Zero.
Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.
Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.
Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.
Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.
Lean is a theorem prover and programming language with a small trusted core based on dependent typed theory, aiming to bridge the gap between interactive and automated theorem proving.
This package contains leanproject, a supporting tool for Lean mathlib, a mathematical library for the Lean theorem prover.
Lean is a theorem prover and programming language with a small trusted core based on dependent typed theory, aiming to bridge the gap between interactive and automated theorem proving.
Not Quite C (NQC) is a simple language for programming several Lego MINDSTORMS products. The preprocessor and control structures of NQC are very similar to C. NQC is not a general purpose language -- there are many restrictions that stem from limitations of the standard RCX firmware.
LeoCAD is a program for creating virtual LEGO models. It has an intuitive interface, designed to allow new users to start creating new models without having to spend too much time learning the application. LeoCAD is fully compatible with the LDraw Standard and related tools.