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DeepSpeed is a distributed deep learning optimization library and framework designed for the training and inference of massive AI models. It serves as a model parallelism orchestrator and a toolkit for scaling large language models across multiple GPUs and compute nodes. The project distinguishes itself through 3D parallelism orchestration, which combines data, pipeline, and tensor parallelism. It utilizes ZeRO-based memory partitioning to eliminate redundant storage and employs CPU-offload memory management to move weights and optimizer states to system RAM. Additionally, it provides special
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
Transformers is a comprehensive library for machine learning that provides a unified interface for training, fine-tuning, and deploying transformer-based models. It supports a wide range of tasks, including text classification, language modeling, question answering, and sequence-to-sequence translation, while offering specialized architectures for both text and vision processing. The framework includes tools for managing the entire model lifecycle, from data preprocessing and tokenization to distributed training and inference. The library features extensive support for model optimization and
A modular RL library to fine-tune language models to human preferences
Build, personalize and control your own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6
The main features of stochasticai/xturing are: LLM Training and Optimization, Model Training, Model Training and Fine-tuning, Natural Language Processing.
Projects with overlapping indexed features include: optimalscale/lmflow — LMFlow is a comprehensive suite for large language model fine-tuning, context extension, multimodal processing, and… microsoft/deepspeed — DeepSpeed is a distributed deep learning optimization library and framework designed for the training and inference of… huggingface/transformers — Transformers is a comprehensive library for machine learning that provides a unified interface for training,… axolotl-ai-cloud/axolotl — Axolotl is a configuration-driven framework designed for the fine-tuning, evaluation, and quantization of large… artidoro/qlora — This project is a quantized fine-tuning framework for large language models. It implements a low-rank adaptation… alexrozanski/llamachat — Chat with your favourite LLaMA models in a native macOS app.