WBC38_clip_blip

DreamBooth model for the WBC38 category concept trained by zz123ff on the zz123ff/WBC_38category-images dataset.

This is a Stable Diffusion model fine-tuned on the WBC38 category concept with DreamBooth. It leverages CLIP for robust text encoding and BLIP for generating detailed image descriptions, providing enhanced multi-modal conditioning for the diffusion process. It can be used by modifying the instance_prompt: "A high-resolution microscopy image of a white blood cell, exhibiting clear morphological features and detailed textures.".

使用WBC38类别概念的模型，由 zz123ff 基于 zz123ff/WBC_38category-images 数据集训练。

这是一个基于WBC38类别图像数据集微调得到的稳定扩散模型，采用DreamBooth进行训练。模型结合了CLIP用于文本编码和BLIP用于图像描述生成，从而为扩散过程提供了更准确的多模态条件信息。您可以通过修改 instance_prompt 来使用此模型："A high-resolution microscopy image of a white blood cell, exhibiting clear morphological features and detailed textures."。

Description / 描述

This model was fine-tuned on the WBC38 category images dataset for medical cell classification tasks. During training, CLIP was used for extracting robust text features, and BLIP was employed to generate detailed image descriptions, enhancing the model's conditioning.

该模型基于WBC38类别图像数据集进行了微调，主要用于医学细胞分类任务。在训练过程中，采用CLIP进行文本特征提取，并使用BLIP生成详细的图像描述，从而为模型提供了更好的多模态条件信息。