曹植大语言模型

曹植大语言模型

曹植大模型管理平台(LLMP,large language model platform)可应用于对自研及开源大模型集中管理、调度、扩展;实现模型fine-tuning;实现训练数据管理、模型训练、模型评估、模型服务、指令Prompt工程、模型训练监控、GPU集群监控等的全方位管理,广泛应用于金融、工业制造、政府等具有文本内容 生成场景、知识管理及问答场景的行业,为企业构建规范的大模型管理及训练执行流程,将数据、模型、服务、指令管理及系统监控等流程规范化并实现有效闭环,手把手式引导企业构建完善的大模型运维模式及管理体系。
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VALL-E

VALL-E

VALL-E is a neural codec language model using discrete codes derived from an off-the-shelf neural audio codec model, and regard TTS as a conditional language modeling task rather. VALL-E emerges in-context learning capabilities and can be used to synthesize high-quality personalized speech with only a 3-second enrolled recording of an unseen speaker as a prompt. We also extend VALL-E and train a multi-lingual conditional codec language model. VALL-E X can generate high-quality speech in the target language via just one speech utterance in the source language as a prompt while preserving the unseen speaker’s voice, emotion, and acoustic environment.
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