llama-joycaption-beta-one-hf-llava

模型介绍

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.

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

公开评测与运行配置

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。

常见问题

资料来源与可追溯记录

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。