M

Machine Learning

🔧🔗https://github.com/HumanSignal/label-studio-ml-backend

Configs and boilerplates for Label Studio's Machine Learning backend

🔧🔗https://github.com/andrewkchan/yalm

Yet Another Language Model: LLM inference in C++/CUDA, no libraries except for I/O

🔧🔗https://github.com/transformerlab/galleries

Galleries for Models, Datasets, and Plugins used by Transformer Lab

🔧🔗https://github.com/MinishLab/tokenlearn

Pre-train Static Word Embeddings

🔧🔗github.com/bytedance/CausalMatch

CausalMatch is a research project aimed at integrating cutting-edge machine learning and econometrics methods to bring about automation in decision-making processes

🔧🔗https://github.com/microsoft/Trace End-to-end Generative Optimization for AI Agents

🔧🔗https://github.com/pytorch/serve

Serve, optimize and scale PyTorch models in production

https://github.com/Lightning-AI/tutorials Collection of Pytorch lightning tutorial form as rich scripts automatically transformed to ipython notebooks. 🔗 https://lightning-ai.github.io/tutorials

🔧🔗https://github.com/poloclub/wizmap

Explore and interpret large embeddings in your browser with interactive visualization! 📍

https://github.com/Lightning-AI/lightning-Habana Lightning support for Intel Habana accelerators.

🔧🔗https://github.com/takara-ai/go-attention

A full attention mechanism and transformer in pure go.

🔧🔗https://gitlab.com/gitlab-org/modelops/mlops/gitlab-mlops

A Python client for integrating GitLab's MLOps features, specifically designed to leverage GitLab's experiment tracking and model registry capabilities. This client simplifies the management of machine learning workflows by combining MLflow's flexibility with GitLab's powerful MLOps tools.

🔧🔗https://github.com/takara-ai/SwarmFormer

A pytorch implementation of SwarmFormer for text classification.

🔧🔗https://github.com/google/uncertainty-baselines High-quality implementations of standard and SOTA methods on a variety of tasks.

🔧🔗https://github.com/jennyzzt/LLM_debate_on_ARC

LLM Debate on ARC dataset

https://github.com/princeton-nlp/CharXiv CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs

🔧🔗https://github.com/pytorch/pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

🔧🔗https://github.com/lutzroeder/netron Visualizer for neural network, deep learning and machine learning models

https://github.com/Upsonic/On-Prem Self-Driven Autonomous Python Libraries

🔧🔗https://github.com/huggingface/speech-to-speech

Speech To Speech: an effort for an open-sourced and modular GPT4-o