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Evaluate your LLM's response with Prometheus and GPT4 💯
🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX
SGLang is yet another fast serving framework for large language models and vision language models.
A high-throughput and memory-efficient inference and serving engine for LLMs
Code for the ICML 2024 paper "Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment"
RewardBench: the first evaluation tool for reward models.
An Easy-to-use, Scalable and High-performance RLHF Framework (70B+ PPO Full Tuning & Iterative DPO & LoRA & Mixtral)
ms-swift: Use PEFT or Full-parameter to finetune 300+ LLMs or 50+ MLLMs. (Qwen2, GLM4v, Internlm2.5, Yi, Llama3.1, Llava-Video, Internvl2, MiniCPM-V, Deepseek, Baichuan2, Gemma2, Phi3-Vision, ...)
A WebUI for Efficient Fine-Tuning of 100+ LLMs (ACL 2024)
Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform
A framework for few-shot evaluation of language models.
A curated list of reinforcement learning with human feedback resources (continually updated)
Cycle-consistent Generative Adversarial Network (CycleGAN) with Convolutional Block Attention Module (CBAM) - Cycle-CBAM. Modified UNet with CBAM - CBAM-UNet.
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.
Non-official implement of Paper:CBAM: Convolutional Block Attention Module
[ACL 2024] Code for the paper "ALaRM: Align Language Models via Hierarchical Rewards Modeling"
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
This repository contains the example of fine-tuning panoptic segmentation model.
This repository contains code used to train U-Net on a multi-class segmentation dataset.
This repository contains demos I made with the Transformers library by HuggingFace.
A JAX research toolkit for building, editing, and visualizing neural networks.
Tree edit distance using the Zhang Shasha algorithm