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An Open-source Toolkit for LLM Development
The main features of alpha-vllm/llama2-accessory are: Language Model Development, Vision Language Models.
Projects with overlapping indexed features include: huggingface/transformers — Transformers is a comprehensive library for machine learning that provides a unified interface for training,… nvidia/megatron-lm — Megatron-LM is a distributed transformer training library and large language model training framework designed to… oxford-cs-deepnlp-2017/lectures — This repository is a deep learning for natural language processing course and curriculum. It provides educational… alibaba/conv-llava — ConvLLaVA: Hierarchical Backbones as Visual Encoder for Large Multimodal Models. apple/ml-aim — This repository provides the code and model checkpoints for AIMv1 and AIMv2 research projects. andrewyng/aisuite — This project is a framework for managing generative AI services through a unified provider interface and adapter…
Megatron-LM is a distributed transformer training library and large language model training framework designed to scale models across thousands of GPUs. It functions as a GPU-optimized deep learning toolkit and a scaling engine for mixture-of-experts architectures, enabling the training of models with hundreds of billions of parameters. The project implements multi-dimensional model parallelism, combining tensor, pipeline, data, expert, and context-based workload distribution. It specifically optimizes mixture-of-experts architectures through integrated memory and communication improvements t
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
This repository is a deep learning for natural language processing course and curriculum. It provides educational material and guides focused on neural network architectures used for processing natural language, speech signals, and text classification. The content includes instructional tutorials on sequence modeling and neural language modeling, covering the implementation of n-gram and recurrent neural networks. It also provides a framework for studying word embeddings to map linguistic meanings into numerical representations. The curriculum covers a broad range of capabilities, including
ConvLLaVA: Hierarchical Backbones as Visual Encoder for Large Multimodal Models