A 4kb framework for creating sturdy frontend applications
like `chown -R`
A simple parser/writer for the Session Description Protocol
Streaming Boyer-Moore-Horspool searching for node.js
Trim newlines from the start and/or end of a string
Declaratively encode and decode binary data
ARIMA, SARIMA, SARIMAX and AutoARIMA models for time series analysis and forecasting
R dictionary for cspell.
Load node modules according to tsconfig paths, in run-time or via API.
Generate llms.txt files to train large language models on your Starlight documentation website
A small module to read JSON files.
Module to match url by pattern with wildcard
Train a fast (FIFO) queue with a rollback mechanism. Behind the scenes it uses 2 arrays to simulate and perform fast shifting and popping operations without using the Array#shift() method..
A validation & parsing library for TypeScript
Declaratively encode and decode binary data
Small library to parse file listings into JavaScript objects
Node.js FastText
Split lines into an array of lines
Outlook Item File (.msg) reader in JavaScript Npm Module
This is a wrapper module over brain.js intended to perform text classification.
Generate a RSA PEM key pair from pure JS
TypeScript port of tcvdb_text — BM25 sparse vector encoder for Tencent Cloud VectorDB
Strict DER signature encoding/decoding.
gulp plugin to delete matched file based on RegExp Obj
Training & Optimization library with autograd, LoRA, quantization, and model merging
Distillation benchmarking and hyperparameter sweep tool
Shared infrastructure for entrenar CLI tools
End-to-end knowledge distillation CLI
SafeTensors model inspection and format conversion
LoRA/QLoRA configuration optimizer and memory planner
Interactive REPL for HuggingFace model exploration and distillation
WASM bindings for Entrenar training monitor
A component to manage Lyquor DNS and TLS certificate.
This crate is a Rust port of Google's BERT create pretraining data.
Kubernetes Custom Resource Bindings
Training utilities for Echo State Networks: ridge/lasso readout solvers, ESN builder helpers, and optional static code generation for embedded inference.
This gem is deprecated in favor of train.
Ruby Scientist and Graphics is a practical data science toolkit for Ruby. It includes a lightweight built-in DataFrame for loading, cleaning, and transforming data; quick descriptive statistics and correlations; charting via Gruff (bar and line); and simple ML utilities (linear regression and k-means)—all behind a small, unified, pandas-inspired API. Key features: - Load data from CSV and JSON. - Clean and transform (remove/add columns, handle missing values, limit rows). - Describe datasets and compute correlations quickly. - Create bar and line charts with customization options. - Train/predict with linear regression; cluster with k-means. - Save/load project state (data + trained model) and run simple pipelines. - Optional backend adapters (e.g., Rover) while keeping the same API. Ideal for analysts and developers who want to explore data in Ruby without relying on Python or R. Note: plotting via Gruff uses rmagick, which requires ImageMagick installed on the system.