Bram Vanroy commited on
Commit
e10ccfa
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1 Parent(s): 05de9a6

update typos

Browse files
Files changed (2) hide show
  1. app.py +3 -3
  2. utils.py +1 -1
app.py CHANGED
@@ -10,11 +10,11 @@ from utils import get_resources, LANGUAGES, translate
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  import streamlit as st
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  st.set_page_config(
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- page_title="Text-to-AMR demo by Bram Vanroy",
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  page_icon="πŸ‘©β€πŸ’»"
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  )
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- st.title("πŸ‘©β€πŸ’» Multilingual text to AMR")
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  if "text" not in st.session_state:
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  st.session_state["text"] = ""
@@ -107,7 +107,7 @@ st.markdown("""
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  st.markdown("""[Abstract meaning representation](https://aclanthology.org/W13-2322/) (AMR)
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  is a semantic framework to describe meaning relations of sentences as graphs. In the SignON project, AMR is used as
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  an interlingua to translate between modalities and languages. To this end, I built MBART models for the task of
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- generating linearized AMR representations from an input sentence, which is show-cased in this demo.
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  """)
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  import streamlit as st
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  st.set_page_config(
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+ page_title="Multilingual text-to-AMR demo by Bram Vanroy",
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  page_icon="πŸ‘©β€πŸ’»"
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  )
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+ st.title("πŸ‘©β€πŸ’» Multilingual text-to-AMR")
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  if "text" not in st.session_state:
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  st.session_state["text"] = ""
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  st.markdown("""[Abstract meaning representation](https://aclanthology.org/W13-2322/) (AMR)
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  is a semantic framework to describe meaning relations of sentences as graphs. In the SignON project, AMR is used as
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  an interlingua to translate between modalities and languages. To this end, I built MBART models for the task of
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+ generating AMR representations from an input sentence, which is show-cased in this demo.
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  """)
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utils.py CHANGED
@@ -3,12 +3,12 @@ from typing import Tuple, Union, Dict, List
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  from multi_amr.data.postprocessing_graph import ParsedStatus
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  from multi_amr.data.tokenization import AMRTokenizerWrapper
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  from optimum.bettertransformer import BetterTransformer
 
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  import streamlit as st
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  import torch
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  from torch.quantization import quantize_dynamic
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  from torch import nn, qint8
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  from transformers import MBartForConditionalGeneration, AutoConfig
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- import penman
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  @st.cache_resource(show_spinner=False)
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  from multi_amr.data.postprocessing_graph import ParsedStatus
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  from multi_amr.data.tokenization import AMRTokenizerWrapper
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  from optimum.bettertransformer import BetterTransformer
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+ import penman
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  import streamlit as st
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  import torch
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  from torch.quantization import quantize_dynamic
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  from torch import nn, qint8
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  from transformers import MBartForConditionalGeneration, AutoConfig
 
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  @st.cache_resource(show_spinner=False)