ChatLiterature / hay /model.py
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from haystack.nodes import PromptNode, PromptTemplate
from haystack.nodes import AnswerParser
from haystack.nodes import TransformersSummarizer
from haystack import Document
def prompting_model():
'''
Define a prompt node in haystack pipeline
'''
prompt_node = PromptNode(model_name_or_path="facebook/galactica-125m", default_prompt_template="deepset/question-answering-per-document")
# prompt_node = PromptNode(model_name_or_path="facebook/opt-350m", default_prompt_template=lfqa_prompt)
return prompt_node
def summarize():
'''
Use a summarizer node, to summarize the output of generator
To remove redundancy/repitition
'''
summarizer = TransformersSummarizer(model_name_or_path="google/pegasus-xsum")
return summarizer