oLLM is a Python library for running large-context Transformers on NVIDIA GPUs by offloading weights and KV-cache to SSDs. It supports models like Llama-3, GPT-OSS-20B, and Qwen3-Next-80B, enabling up to 100K tokens of context on 8-10 GB GPUs without quantization.
An article detailing the author's experience replacing bash scripts with Python, outlining the improvements in readability, error handling, and testability, as well as the challenges encountered during the migration.
The Model Context Protocol (MCP) is a new open protocol that allows AI models to interact with external systems in a standardized, extensible way. In this tutorial, you’ll install MCP, explore its client-server architecture, and work with its core concepts: prompts, resources, and tools.
A curated collection of Awesome LLM apps built with RAG, AI Agents, Multi-agent Teams, MCP, Voice Agents, and more. This repository features LLM apps that use models from OpenAI, Anthropic, Google, xAI and open-source models like Qwen or Llama.
A comprehensive guide covering the most critical machine learning equations, including probability, linear algebra, optimization, and advanced concepts, with Python implementations.
The author discusses a shift in approach to clustering mixed data, advocating for starting with the simpler Gower distance metric before resorting to more complex embedding techniques like UMAP. They introduce 'Gower Express', an optimized and accelerated implementation of Gower.
This article details a hands-on approach to modeling rare events in time series data using Python. It covers data exploration, defining extreme events, fitting distributions (GEV, Weibull, Gumbel), and evaluating model performance using metrics like log-likelihood, AIC, and BIC. The example uses weather data and provides code snippets for implementation.
This article explores the impact of hyperparameters on random forests, both in terms of performance and visual representation. It compares the performance of a default random forest with tuned decision trees and examines the effects of various hyperparameters like `n_estimators`, `max_depth`, and `ccp_alpha` using visualizations of individual trees, predictions, and errors.
The fast, feature-rich, GPU based terminal emulator. It's capable, scriptable, composable, cross-platform, and innovative.
An open source web crawler that searches the internet. It's a minimal, real-time web search CLI that searches the internet for you. Enter a query and get search results as JSON (title, url, published_date), sorted by recency.
