# Dialogue Summarization

A fine-tuned version of the google/flan-t5-base model for dialogue summarization tasks, using PEFT for parameter-efficient fine-tuning

This model is a text summarization model fine-tuned on the samsum dataset based on google/pegasus-cnn_dailymail, specifically designed for dialogue summarization tasks.

BART Large CNN is a pre-trained model based on the BART architecture, specifically designed for text summarization tasks.

This is a T5 text summarization model fine-tuned on the SAMSum dataset, suitable for dialogue and conversation summarization tasks.

SummLlama3.1-8B is a text summarization model initialized from Llama3.1-8B-Instruct, optimized through large-scale summarization feedback via Direct Preference Optimization (DPO), excelling in fidelity, completeness, and conciseness.

This is a dialogue summarization model based on the T5-base architecture, fine-tuned using LoRA technology, specifically designed for efficient dialogue summarization.

This model is based on the Pegasus architecture and fine-tuned on the SAMSUM dataset for English dialogue summarization.

This model is a fine-tuned version of google/flan-t5-base on the samsum dialogue summarization dataset, specifically designed for dialogue summarization tasks.

English dialogue summarization model fine-tuned based on BART-large-cnn, specifically optimized for the Samsung/samsum dataset

A dialogue summarization model based on the BART-large architecture, specifically fine-tuned for the SAMSum corpus, capable of efficiently generating abstract summaries of dialogues.

This model is a fine-tuned version of google/pegasus-cnn_dailymail on the samsum dataset, primarily used for text summarization tasks.

A dialogue summarization model fine-tuned based on BART-large-xsum, specifically optimized for the SamSum dialogue dataset

A dialogue summarization model based on the BART architecture, specifically fine-tuned for the SAMSum dialogue dataset

A dialogue summarization generation model fine-tuned on the SAMSum dataset based on the BART-large architecture

A summarization model based on the Long-T5 architecture, supporting multilingual text summarization tasks.

A text generation model fine-tuned on the samsum dialogue summarization dataset based on Google's flan-t5-base model, excelling in dialogue summarization tasks

A dialogue summarization model based on the BART architecture, specifically fine-tuned for the SAMSum corpus, capable of generating high-quality dialogue summaries.

A text generation model fine-tuned on the samsum dialogue summarization dataset based on Google's flan-t5-base model

This model is a text summarization model fine-tuned on the samsum dataset based on facebook/bart-large-xsum, specializing in generating dialogue summaries.

A summary generation model fine-tuned on the stacked-samsum-1024 dataset based on google/flan-t5-large, using stacked summarization method to improve information extraction capability

A dialogue summarization model fine-tuned on t5-small, trained on the samsum dataset

This model is a fine-tuned version of facebook/bart-base on the samsum dataset, specifically designed for summarization tasks.

This is a sequence-to-sequence model based on the BART architecture, specifically designed for dialogue summarization tasks.

This model is a seq2seq model based on the BART architecture, specifically designed for dialogue summarization tasks, fine-tuned on the SAMSum dataset.

A dialogue summarization model based on the BART-large architecture, specifically fine-tuned on the SAMSum dialogue dataset, capable of generating high-quality dialogue summaries.

A dialogue summarization model fine-tuned based on BART-large architecture, trained on the SAMSum dataset, specifically optimized for dialogue text summarization

This model is a BART-large-xsum model fine-tuned on the Samsum dataset, specifically designed for dialogue summarization tasks.

A dialogue summarization model based on the BART-large architecture, fine-tuned specifically for the SAMSum corpus, suitable for generating dialogue summaries.

A lightweight dialogue summarization model fine-tuned on the SAMSum dataset, trained using Amazon SageMaker and Hugging Face containers

A dialogue summarization model based on BART-base architecture, trained using Amazon SageMaker and Hugging Face deep learning containers, suitable for the SAMSum dataset.

This model is based on the BART architecture, fine-tuned on the SAMSum dialogue dataset for abstractive text summarization, specifically designed for generating dialogue summaries.

DialogLM is a pretrained model based on the Longformer Encoder-Decoder (LED) architecture, specifically designed for long dialogue understanding and summarization tasks.

DialogLM is a pre-trained model based on the Longformer-Encoder-Decoder (LED) architecture, specifically designed for long dialogue understanding and summarization tasks.