# Large-scale pre-training fine-tuning

This is a sentence transformer model fine-tuned on xlm-roberta-large, which can map text to a 1024-dimensional vector space and support multilingual semantic understanding tasks.

A Korean sentence embedding model fine-tuned based on multilingual-e5-large, supporting 1024-dimensional vector space mapping, suitable for tasks such as semantic similarity calculation

A Cantonese automatic speech recognition (ASR) model fine-tuned based on OpenAI Whisper Large V2, trained on the Common Voice 11.0 Cantonese dataset with a character error rate (CER) of 6.21%.

This model is a Turkish speech recognition model fine-tuned on the Common Voice dataset based on facebook/wav2vec2-xls-r-300m

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset, primarily used for Tamil speech recognition tasks.

An audio classification model based on the XLS-R architecture, designed to distinguish between adult and child speech.

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on a general speech dataset, suitable for speech recognition tasks.

This is an automatic speech recognition (ASR) model fine-tuned on the Odia dataset based on facebook/wav2vec2-xls-r-300m, specifically designed for Odia speech-to-text tasks.