A framework for few-shot evaluation of language models.

A Datacenter Scale Distributed Inference Serving Framework

FlashInfer: Kernel Library for LLM Serving

OpenAI-Compatible RESTful APIs for Amazon Bedrock

Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.

AutoML Two-Sample Test

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)

Library for automatic retraining and continual learning

Easy, fast and very cheap training and inference on AWS Trainium and Inferentia chips.

A Library for Uncertainty Quantification.

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…

SciPy library main repository

Reproducibility code for Efficient Aggregated Kernel Tests using Incomplete U-statistics, by Schrab, Kim, Guedj and Gretton: https://arxiv.org/abs/2206.09194 NeurIPS 2022

A little Python script to collect LaTeX sources for upload to the arXiv.

Implementation of Deep Linear Discriminant Analysis (DeepLDA)

An implementation of Deep Linear Discriminant Analysis (DeepLDA) in Keras

Cocreate Shared Whiteboard/Drawing

This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).

PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Built by researchers, for research.

An implementation of the kernel conditional moment (KCM) tests.

An open-source Python framework for hybrid quantum-classical machine learning.

NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.