Directory
Models and machine learning covers model hubs, research papers, training guides and evaluation tools. The topic mixes practical resources with reference material, so you will find repositories that host downloadable models next to sites that explain how a technique works. Some entries are collections of papers or benchmarks, and others are tutorials that walk through fine-tuning or deployment. It pays to compare the model licence, the training data, the hardware needed and the date of the last update. The field moves quickly, so verify version notes on the source before you build on anything listed here.
Bloop is a fast code search engine written in Rust, distributed through GitHub releases. The repository was archived by its owner on Jan 2, 2025, and is now read-only. Release notes for versions v0.6.0 to v0.6.5 list changes such as explaining files in a user-set language, adding multiple files to code studio, code coloring for COBOL, and alternative input types for Chinese users.
Bodywork is a command line tool that deploys machine learning pipelines to Kubernetes, handling containers and orchestration. Any pipeline stage runs either a batch job or a long-running process. It is presented as a lightweight alternative to Kubeflow or building a platform around workflow tools such as Apache Airflow, Argo Workflows or Dagster. Stages are defined as Python modules or Jupyter notebooks and configured in a single bodywork.yaml file.
Boring Report: News by AI - Information Without the Noise.
Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
This repository collects notebooks that explore Retrieval-Augmented Generation (RAG) for various applications, from introductory to advanced implementations. It includes a full_basic_rag.ipynb starter and notebooks on multi-querying, routing, query construction, indexing, and advanced retrieval. The materials cover environment setup, data loading, embedding generation, and vector store configuration with ChromaDB or Pinecone.
The iOS and OS X neural network framework.
Bread Dataset Viewer is a VS Code extension for viewing and handling large datasets. It opens JSONL, Parquet, CSV, TSV, JSON, and Arrow/Feather files by streaming and lazy-loading data, and provides Cards, Table, and Raw views. It includes 16 production LLM tokenizers from GPT, Claude, Llama, and Qwen for chat completion data.
Breeze is a numerical processing library for Scala.
brexhq/prompt-engineering is a GitHub repository containing Brex's Prompt Engineering Guide. It provides tips and tricks for working with Large Language Models such as OpenAI's GPT-4, with content covering the definition of large language models, an incomplete history of language models, and the concept of prompts.
Theano based library for deep and recurrent neural networks.
A curated GitHub list of papers and tools covering LLM threats and vulnerabilities from a security and privacy standpoint. It includes paper summaries, key takeaway points, citations in a bib file, and frameworks and taxonomies such as OWASP Top 10 for LLM Applications.
broadn is an AI tool designed for manufacturing sales operations. It automates quoting and order processing from inbound emails to enterprise resource planning (ERP) systems, converting unstructured requests for quotes and sales orders into clean outputs including quotes sent to CRM and orders sent to ERP. It offers features such as instant quoting, rule-based discounts, product configuration, and margin control, and has launched Agent Herbie for operation in secure or air-gapped offline environments.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
burn is a next-generation tensor library and deep learning framework developed by tracel-ai. It is designed to prioritize flexibility, efficiency, and portability, with available resources covering use with Rust, its ecosystem, supported backends, and training and inference functionality.
Butternut AI is an AI website builder for small businesses that generates a site from a business name and description. It includes hosting, SSL, a free custom domain for the first year, SEO features, an AI blog writer and an AI chatbot, with Starter and Pro plans.
Caffe is a deep learning framework developed by Berkeley AI Research and community contributors, designed with expression, speed, and modularity in mind. It is released under the BSD 2-Clause license and includes associated reference models.
Cal.ai provides machine-learning models, research, training resources, or evaluation tools.
Authors:, Dexter Storey, Ted Spare.
Calculated Risk is an economics and finance blog focused on the housing market. In January 2026 the author announced stopping daily updates after 21 years, moving to a weekly economic summary newsletter and a real estate newsletter.
CAMEL is an open-source community and framework for studying multi-agent systems at scale. It implements and supports various agents, tasks, prompts, models and simulated environments, and describes design principles including evolvability, scalability, statefulness and code-as-prompt.
Role-playing approach for LLMs and auto-agents like BabyAGI & AutoGPT.
Candle is a minimalist machine learning framework for Rust with a focus on performance, including GPU support, and ease of use. It provides examples and online browser demos for models such as whisper, LLaMA2, T5, yolo and Segment Anything.
Model interpretability and understanding library for PyTorch.
A general classifier module to allow Bayesian and other types of classifications.
