# Large-scale Dataset

A vision-language model trained on the MetaCLIP-400M dataset, supporting zero-shot image classification tasks

Llama 2 is an open-source large language model developed by Meta, supporting multiple languages including English and Arabic.

OpenCLIP model based on ResNet50 architecture and trained on the CC12M dataset, supporting zero-shot image classification tasks.

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

EVA02 is a large-scale vision-language model based on the CLIP architecture, supporting zero-shot image classification tasks.

WavLM is a large-scale self-supervised pretrained speech model developed by Microsoft, pretrained on 16kHz sampled speech audio, suitable for various speech processing tasks.

A Vision Transformer model pretrained on the ImageNet-21k dataset for image classification tasks.

Sentence embedding model based on MPNet architecture, mapping text to a 768-dimensional vector space, suitable for semantic search and sentence similarity calculation