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Financial data platform for analysts, quants and AI agents.
EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL
This repository contains the code for SFT, RLHF, and DPO, designed for vision-based LLMs, including the LLaVA models and the LLaMA-3.2-vision models.
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Supercharge Your LLM Application Evaluations 🚀
Fantastic Data Engineering for Large Language Models
The official Python library for the OpenAI API
From Chain-of-Thought prompting to OpenAI o1 and DeepSeek-R1 🍓
Codebase for Merging Language Models (ICML 2024)
🚀 Efficient implementations of state-of-the-art linear attention models
Open-Sora: Democratizing Efficient Video Production for All
Clustering and Ranking: Diversity-preserved Instruction Selection through Expert-aligned Quality Estimation
Machine Learning Engineering Open Book
[ACL 2024] FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models
[ACL 2024] An Easy-to-use Instruction Processing Framework for LLMs.
JsonTuning: Towards Generalizable, Robust, and Controllable Instruction Tuning
[ICML'24] Data and code for our paper "Training-Free Long-Context Scaling of Large Language Models"
Chat language model that can use tools and interpret the results
[ICML'24 Spotlight] LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning
OpenChat: Advancing Open-source Language Models with Imperfect Data
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Deita: Data-Efficient Instruction Tuning for Alignment [ICLR2024]
This is a collection of research papers for Self-Correcting Large Language Models with Automated Feedback.
中文LLaMA-2 & Alpaca-2大模型二期项目 + 64K超长上下文模型 (Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models)
Source code of "Reasons to Reject? Aligning Language Models with Judgments"