Minimal examples of data structures and algorithms in Python
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Minimal examples of data structures and algorithms in Python
JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
DeepInfer: High-performance, large-scale inference framework for DeepSeek models
Image-to-Image Translation in PyTorch
WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Data Apps & Dashboards for Python. No JavaScript Required.
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
Graph Neural Network Library for PyTorch
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Python Backtesting library for trading strategies
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
Saleor Core: the high performance, composable, headless commerce API.
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.
LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar
Universal LLM Deployment Engine with ML Compilation
TranslatedAKShare is an elegant and simple financial data interface library for Python, built for human beings! Open-source financial data interface library
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
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Project documentation with Markdown.