相比于PipeDream采样端到端的训练时间,Varuna将需要采样的数据分解成了如上表所示的7个“元数据”,这些待采样的数据之间是互不影响的,并且可以独立采样,这令Varuna可以利用所有的空闲GPU集群并行采样,进一步缩短了采样时长。通过采样这些“元数据”并基于建模对端到端训练时长做预测,Varuna能够快速决策出新的并行训练...
Paper tables with annotated results for Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
ZeroQuant can significantly reduce training resources and time cost, without requiring the original training data. We demonstrated the scalability of ZeroQuant on a GPT-3-style model with 1.3B parameters (GPT-3-1.3B) and one of the largest open-source language models, G...
Based on a large corpus in the form of code-comment pairs, a deep language model is trained to fulfill such a language translation or summarization task. To encompass and generalize extremely diverse training corpus, mainstream industries keep scaling up the deep ...
The datasets used for training language models typically contain 10–200 GB of raw text data. Loading the whole dataset in RAM can be challenging. Furthermore, the typical pipeline of first running the preprocessing for all data and then pullin...
base_model: The base model, which can be chosen and downloaded according to your needs. The open-source large models are only for learning and experiential purposes. The current default is TheBloke/vicuna-7B-1.1-HF. data_path: The path of your personalized training data and domain-s...
Today’s state-of-the-art large language models (LLMs) can have more than 100 billion parameters — a number that is regularly rising — and have achieved astounding performance on complex natural language processing (NLP) tasks such as writing articles,...
Research into methods for improving the performance of large language models (LLMs) through fine-tuning, retrieval-augmented generation (RAG) and soft-prompting has tended to focus on the use of highly technical or high-cost techniques, making many of the newly discovered approaches comparatively in...
登录/注册 巴比龙 北京邮电大学 计算机科学技术博士 Papers | MoE-LLaVA: Mixture of Experts for Large Vision-Language ModelsFor Large Vision-Language Models (LVLMs), scaling the model can effectively improve performance. However, expanding model parameters significantly increases the training and...
Java Microsoft Build of OpenJDK Java API 瀏覽器 依產品排序的 JAVA 文件 資源 版本 Azure SDK for Java Preview 搜尋 適用於 Java 的 Azure SDK 檔 com.azure.verticals.agrifood.farming com.azure.ai.anomalydetector com.azure.ai.anomalydetector.models com.azure.media.videoanalyzer.edge.mode...