Llama-OuteTTS-1.0-1B

모델 소개

> [!IMPORTANT] > **Important Sampling Considerations** > > When using OuteTTS version 1.0, it is crucial to use the settings specified in the Sampling Configuration section. > > The **repetition penalty implementation** is particularly important - this model requires penalization applied to a **64-token recent window**, > rather than across the entire context window. Penalizing the entire context will cause the model to produce **broken or low-quality output**. > > Currently, **llama.cpp** delivers the most reliable and consistent output quality by default. > Both **llama.cpp** and **EXL2** support this windowed sampling approach, while **Transformers** doesn't. > > To address this limitation, I've implemented a **windowed repetition penalty** for the **Hugging Face Transformers** backend in the **OuteTTS** library, > which significantly improves output quality and resolves sampling issues, providing comparable results to llama.cpp. This update brings significant improvements in speech synthesis and voice cloning—delivering a more powerful, accurate, and user-friendly experience in a compact size. The model is designed to be used with a speaker reference. Without one, it generates random vocal characteristics, often leading to lower-quality outputs. The model inherits the referenced speaker's emotion, style, and accent. When transcribing to other languages with the same speaker, you may observe the model retaining the original accent.

주요 특징

特点摘要待依据来源补齐，不凭模型名称推断能力。

한계 및 유의 사항

구체적 한계를 판단할 출처가 부족합니다. 실제 성능, 지연, 데이터 정책, 라이선스와 버전 수명을 확인하세요.

출처별 요금 및 비용 분석

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공개 평가 및 실행 설정

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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출처 및 추적 기록

许可证：cc-by-nc-sa-4.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。