metadata
license: mit
datasets:
- ai-forever/paper_persi_chat
language:
- en
pipeline_tag: conversational
This is a weights storage for the PaperPersiChat pipeline models.
The pipeline is presented in the paper PaperPersiChat: Scientific Paper Discussion Chatbot using Transformers and Discourse Flow Management
Installation
git lfs install
git clone https://huggingface.co/ai-forever/paper_persi_chat
Usage
- Full pipeline:
See more details on https://github.com/ai-forever/paper_persi_chat
- Single models:
Inference examples: 
Three models (Summarizer, QA module and Response Generator) can be imported using transformers library after weights downloading:
from transformers import BartForConditionalGeneration, BartTokenizer
model_name_or_path = 'paper_persi_chat/distilbart_summarizer' # or 'paper_persi_chat/bart_response_generator'
tokenizer = BartTokenizer.from_pretrained(model_name_or_path)
model = BartForConditionalGeneration.from_pretrained(model_name_or_path).to('cuda')
from transformers import pipeline
model = pipeline("question-answering", model='paper_persi_chat/deberta_qa')
pred = model(question,
context,
max_seq_len=384,
doc_stride=64,
max_answer_len=384)
Citation
If you find our models helpful, feel free to cite our publication PaperPersiChat: Scientific Paper Discussion Chatbot using Transformers and Discourse Flow Management:
@inproceedings{chernyavskiy-etal-2023-paperpersichat,
title = "{P}aper{P}ersi{C}hat: Scientific Paper Discussion Chatbot using Transformers and Discourse Flow Management",
author = "Chernyavskiy, Alexander and
Bregeda, Max and
Nikiforova, Maria",
booktitle = "Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue",
month = sep,
year = "2023",
address = "Prague, Czechia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.sigdial-1.54",
pages = "584--587",
}