# Low-Resource Fine-Tuning

A Whisper Small model fine-tuned for Arabic recitation of the Quran, capable of accurately identifying and transcribing Quran recitation content.

Mol-LLaMA is a large language model for molecular understanding based on Llama-3.1-8B-Instruct, focusing on the comprehension and reasoning of molecular properties in biology, chemistry, and medical fields.

A Japanese large language model fine-tuned specifically for role-playing, based on sbintuitions/sarashina2.2-3b-instruct-v0.1

FANformer-1B is an autoregressive model enhanced with innovative periodic mechanisms for language modeling, featuring 1.1 billion non-embedding parameters and trained on 1 trillion tokens.

This is a fine-tuned sentence transformer model based on sentence-transformers/all-mpnet-base-v2, designed to map text into a 768-dimensional vector space, supporting tasks such as semantic similarity computation.

A cross-encoder model fine-tuned based on sentence-transformers/all-mpnet-base-v2, used to evaluate the coherence and relevance of dialogue responses.

A text-to-speech model capable of controlling rich speech styles through textual style prompts

A Polish dialogue model fine-tuned on Mistral-7B-v0.2, focused on delivering smooth and natural conversational experiences

A Russian dialogue summarization model fine-tuned on d0rj/rut5-base-summ, trained on the DialogSum dataset

A summary generation model fine-tuned on an unknown dataset based on Google's mT5 model, supporting multilingual text summarization tasks

A text summarization model fine-tuned based on barthez-orangesum-title, specializing in generating headline-style summaries

This model is a fine-tuned version of distilbert-base-cased-distilled-squad, suitable for question-answering tasks