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This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
FinRobot: An Open-Source AI Agent Platform for Financial Applications using LLMs 🚀 🚀 🚀
Challenge LLMs to Reason About Reasoning: A Benchmark to Unveil Cognitive Depth in LLMs
A banchmark list for evaluation of large language models.
[EMNLP'23, ACL'24] To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.
A repo lists papers related to LLM based agent
A collection of AWESOME things about Graph-Related LLMs.
The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.
A framework for the evaluation of autoregressive code generation language models.
[ICML 2023] Data and code release for the paper "DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation".
🐙 OctoPack: Instruction Tuning Code Large Language Models
Supercharge Your LLM Application Evaluations 🚀
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
List of language agents based on paper "Cognitive Architectures for Language Agents"
Awesome things about LLM-powered agents. Papers / Repos / Blogs / ...
Train transformer language models with reinforcement learning.
Firefly: 大模型训练工具,支持训练Qwen2.5、Qwen2、Yi1.5、Phi-3、Llama3、Gemma、MiniCPM、Yi、Deepseek、Orion、Xverse、Mixtral-8x7B、Zephyr、Mistral、Baichuan2、Llma2、Llama、Qwen、Baichuan、ChatGLM2、InternLM、Ziya2、Vicuna、Bloom等大模型
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
Aligning pretrained language models with instruction data generated by themselves.
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.