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MiniGPT-4: Enhancing Vision-language Understanding with Advanced Large Language Models

The release repo for "Vicuna: An Open Chatbot Impressing GPT-4"

gpt4all: a chatbot trained on a massive collection of clean assistant data including code, stories and dialogue

Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform

Instruct-tuning LLaMA on consumer hardware

WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)

Plug and play modules to optimize the performances of your AI systems 🚀

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

A playbook for systematically maximizing the performance of deep learning models.

PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

A tool to help researchers and product teams understand datasets with the goal of improving data quality, and mitigating fairness and bias issues.

Lightning ⚡️ fast forecasting with statistical and econometric models.

Tensor search for humans.

Automatic architecture search and hyperparameter optimization for PyTorch

ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

A to Z of ML

Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

TODS: An Automated Time-series Outlier Detection System

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch

NeMo: a toolkit for conversational AI

Visualize large time-series data in plotly

[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.

Cloud-native neural search framework for 𝙖𝙣𝙮 kind of data

The Numenta Anomaly Benchmark

Load Testing ML Microservices for Robustness and Scalability

Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).