# Multimodal Alignment

Hermes Flow is a universal multimodal large language model alignment framework capable of autonomously generating homologous preference data. Through self-play iterative optimization and paired DPO techniques, it seamlessly bridges the gap between multimodal understanding and generation.

Vision Transformer model based on SigLIP, containing only the image encoder part, utilizing original attention pooling mechanism

This is a powerful text-image interleaved input-output model, deeply aligned through the Align Anything algorithm, improving image generation capabilities and human preference alignment.

HPT is a transformer model that aligns different entities into a shared latent space, focusing on the study of expansion behaviors in policy learning.

LanguageBind is a pretrained model that achieves multimodal semantic alignment through language, capable of binding various modalities such as video, audio, depth, and thermal imaging with language to enable cross-modal understanding and retrieval.

LanguageBind is a language-centric multimodal pretraining method that achieves semantic alignment by using language as the bridge between different modalities.

LanguageBind is a language-centric multimodal pretraining method that uses language as the bond between different modalities to achieve semantic alignment across video, infrared, depth, audio, and other modalities.

LanguageBind is a multimodal model that extends video-language pretraining to N modalities through language-based semantic alignment, accepted by ICLR 2024.

LanguageBind is a language-centric multimodal pretraining method that uses language as the bond between different modalities to achieve semantic alignment.

LanguageBind is a language-centric multimodal pretraining method that uses language as the bond between different modalities to achieve semantic alignment across video, infrared, depth, audio, and other modalities.

LanguageBind is a multimodal pretraining framework that extends video-language pretraining to N modalities through language semantic alignment, accepted by ICLR 2024.

LanguageBind is a pretraining framework that achieves multimodal semantic alignment through language as the bond, supporting joint learning of various modalities such as video, infrared, depth, and audio with language.

TinySapBERT is a compact biomedical entity representation model trained on the SapBERT framework, specifically designed for biomedical named entity recognition tasks.

A Turkish text encoder fine-tuned from dbmdz/distilbert-base-turkish-cased, designed to work with CLIP's ViT-B/32 image encoder