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llama-joycaption-beta-one-hf-llava

fancyfeast · llama-joycaption-beta-one-hf-llava

JoyCaption is an image captioning Visual Language Model (VLM) built from the ground up as a free, open, and uncensored model for the community to use in training Diffusion models. Key Features: - **Free and Open**: Always released for free, open weights, no restrictions, and just like bigASP, will come with training scripts and lots of juicy details on how it gets built. - **Uncensored**: Equal coverage of SFW and NSFW concepts. No "cylindrical shaped object with a white substance coming out on it" here. - **Diversity**: All are welcome here. Do you like digital art? Photoreal? Anime? Furry? JoyCaption is for everyone. Pains are being taken to ensure broad coverage of image styles, content, ethnicity, gender, orientation, etc. - **Minimal Filtering**: JoyCaption is trained on large swathes of images so that it can understand almost all aspects of our world. almost. Illegal content will never be tolerated in JoyCaption's training. Automated descriptive captions enable the training and finetuning of diffusion models on a wider range of images, since trainers are no longer required to either find images with already associated text or write the descriptions themselves. They also improve the quality of generations produced by Text-to-Image models trained on them (ref: DALL-E 3 paper). But to-date, the community has been stuck with ChatGPT, which is expensive and heavily censored; or alternative models, like CogVLM, which are weaker than ChatGPT and have abysmal performance outside of the SFW domain.

번역 대기 중입니다. 원문을 표시합니다.

컨텍스트 창미공개
입력 → 출력텍스트、이미지 → 텍스트
모델 웨이트미확인
정보 업데이트2026/11/2 19:16:40
OVERVIEW

모델 소개

JoyCaption is an image captioning Visual Language Model (VLM) built from the ground up as a free, open, and uncensored model for the community to use in training Diffusion models. Key Features: - **Free and Open**: Always released for free, open weights, no restrictions, and just like bigASP, will come with training scripts and lots of juicy details on how it gets built. - **Uncensored**: Equal coverage of SFW and NSFW concepts. No "cylindrical shaped object with a white substance coming out on it" here. - **Diversity**: All are welcome here. Do you like digital art? Photoreal? Anime? Furry? JoyCaption is for everyone. Pains are being taken to ensure broad coverage of image styles, content, ethnicity, gender, orientation, etc. - **Minimal Filtering**: JoyCaption is trained on large swathes of images so that it can understand almost all aspects of our world. almost. Illegal content will never be tolerated in JoyCaption's training. Automated descriptive captions enable the training and finetuning of diffusion models on a wider range of images, since trainers are no longer required to either find images with already associated text or write the descriptions themselves. They also improve the quality of generations produced by Text-to-Image models trained on them (ref: DALL-E 3 paper). But to-date, the community has been stuck with ChatGPT, which is expensive and heavily censored; or alternative models, like CogVLM, which are weaker than ChatGPT and have abysmal performance outside of the SFW domain.

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.

PRICING & COST

출처별 요금 및 비용 분석

요금은 채널, 지역, 설정에 따라 다릅니다. 각 채널 요금은 개별 표시되며 제공사의 통일 공식 요금이 아닙니다.

출처 / 채널입력출력과금 단위수집 시간
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월간 기본 토큰 비용 추정

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추정치에는 캐시 할인, 구간 요금, 멀티모달 추가 요금, 검색, 세금 및 추가 추론 출력이 포함되지 않습니다.

INDEPENDENT BENCHMARKS

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:来源未披露,须进一步核验。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。