# Multi-Dataset Fine-Tuning

A text summarization model fine-tuned based on the BART architecture, specifically designed for generating concise summaries of conversations and news articles.

A Chinese speech recognition model fine-tuned and optimized based on whisper-large-v3, showing significant performance improvements in multiple Chinese speech benchmarks

This is a Thai automatic speech recognition model fine-tuned based on OpenAI's Whisper Large V3 model, achieving a 6.59% word error rate on the Common Voice 13 Thai test set.

A DeBERTa-v3 fine-tuned model for prompt injection detection, designed to identify malicious prompt inputs

QAmembert is a fine-tuned model based on CamemBERT for French question-answering tasks, trained on four French Q&A datasets, supporting both answer-present and no-answer scenarios.

A fine-tuned Brazilian Portuguese abstractive text summarization model based on PTT5, supporting various summarization tasks.

A large BART sequence-to-sequence (text generation) model fine-tuned on 3 paraphrase datasets for sentence rewriting tasks.