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AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Models and examples built with TensorFlow
Financial data platform for analysts, quants and AI agents.
Unified web UI for training and running open models like Qwen, DeepSeek, gpt-oss and Gemma locally.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
LlamaIndex is the leading document agent and OCR platform
aider is AI pair programming in your terminal
TensorFlow code and pre-trained models for BERT
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, i…
Build, run, manage agentic software at scale.
DSPy: The framework for programming—not prompting—language models
PyTorch Tutorial for Deep Learning Researchers
🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…
Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.
Fully open reproduction of DeepSeek-R1
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Download market data from Yahoo! Finance's API
Python Backtesting library for trading strategies
The official repo of Qwen (通义千问) chat & pretrained large language model proposed by Alibaba Cloud.
Zipline, a Pythonic Algorithmic Trading Library
SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]