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Dromedary: towards helpful, ethical and reliable LLMs.
LMFlow is a comprehensive suite for large language model fine-tuning, context extension, multimodal processing, and inference execution. It provides a toolkit for updating model parameters through full tuning or memory-efficient adapter algorithms, alongside an inference engine for executing tuned models via command-line or web-based interfaces. The framework includes a dedicated alignment suite for supervised tuning and reward model training to refine model behavior. It features a context window extender to increase maximum input lengths and a multimodal framework for building chatbots that
LMOps is a research-driven operations framework for optimizing the deployment, fine-tuning, and performance of large language models. It provides a specialized toolkit for foundation model adaptation, inference acceleration, prompt optimization, and context orchestration. The framework distinguishes itself through an inference accelerator that reduces token generation latency by verifying and copying overlapping text spans from reference documents. It also features a prompt engineering optimizer that employs reinforcement learning, beam search, and non-natural language markers to automaticall
Align-anything is a multi-modal large language model alignment framework designed to fine-tune models across text, image, video, and audio. It functions as a distributed training orchestrator and toolkit for implementing preference-based learning to ensure model behaviors match human intentions and values. The framework provides specialized pipelines for Supervised Fine-Tuning and Direct Preference Optimization. It includes a high-performance inference engine wrapper for actor models to reduce sequence generation time and a dedicated training environment for refining vision-language-action mo
This repo contains code and instructions for reproducing the experiments in the paper "RLCD: Reinforcement Learning from Contrast Distillation for Language Model Alignment" (https://arxiv.org/abs/2307.12950), by Kevin Yang, Dan Klein, Asli Celikyilmaz, Nanyun Peng, and Yuandong Tian. RLCD is a…
The main features of facebookresearch/rlcd are: Model Alignment and Feedback, Self-Improvement Methods.
Projects with overlapping indexed features include: ibm/dromedary — Dromedary: towards helpful, ethical and reliable LLMs. microsoft/lmops — LMOps is a research-driven operations framework for optimizing the deployment, fine-tuning, and performance of large… optimalscale/lmflow — LMFlow is a comprehensive suite for large language model fine-tuning, context extension, multimodal processing, and… pku-alignment/align-anything — Align-anything is a multi-modal large language model alignment framework designed to fine-tune models across text,… volcengine/verl — verl is a distributed training system designed for large language model alignment and reinforcement learning. It… uber/ludwig — Ludwig is a declarative machine learning framework designed for training neural networks and large language models…