Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
- artificial-intelligence
- attention-mechanism
- transformers
- computer-vision
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Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
🦉 Data Versioning and ML Experiments
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Open Source Intelligence gathering tool aimed at reducing the time spent harvesting information from open sources.
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Accelerated deep learning R&D
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
A toolkit for reproducible reinforcement learning research.
A deep learning toolkit for healthcare AI: EHR (MIMIC, eICU, OMOP), clinical text, signals and imaging. 30+ models, reproducible pipelines.
The open-source governance layer for AI agents: write the rules declaratively, Bernstein enforces them and produces the verifiable, replayable record. Free, Apache-2.0. https://bernstein.run
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
FactCircuit: an auditable claim-and-evidence verification loop with immutable provenance, staged checks, bounded retrieval, and reproducible evaluation.
An elegant Python interface for visualization on the web platform to interactively generate insights into multidimensional images, point sets, and geometry.
Say It Simply, Test It Properly. Agent-powered strategy research with independent ledger checks and reproducible reports.
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.
A tool that supports one-button reproducible workflows with the Jupyter Notebook and Scons.