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Parent(s):
c417e30
small demo
Browse files- README.md +5 -0
- app.py +53 -0
- requirements.txt +3 -0
README.md
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@@ -11,3 +11,8 @@ license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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## Simple app showcasing the [spacy-to-hf](https://github.com/Ben-Epstein/spacy-to-hf) repo
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Add in your NER Span data and get back a huggingface dataset ready
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for fine-tuning Token Classification!
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app.py
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import streamlit as st
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from spacy_to_hf import spacy_to_hf
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import os
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import spacy
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from datasets import Dataset
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import json
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from json import JSONDecodeError
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try:
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nlp = spacy.load("en_core_web_sm")
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except:
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os.system("python -m spacy download en_core_web_sm")
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st.experimental_rerun()
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demo_option = [
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{
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"text": "Planned to go to the Apple Storefront on Tuesday",
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"spans": [
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{"start": 0, "end": 7, "label": "Action"},
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{"start": 21, "end": 37, "label": "Loc"},
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{"start": 41, "end": 48, "label": "Date"},
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]
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}
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]
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tokenizers = [
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"bert-base-uncased",
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"bert-base-cased",
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"distilbert-base-uncased",
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"distilbert-base-cased",
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"roberta-base",
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]
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tok = st.selectbox("Pick a tokenizer", tokenizers)
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spacy_data = st.text_area("Input your NER Span data here")
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if spacy_data or st.button("Or try an example"):
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run_data = None
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if spacy_data:
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try:
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run_data = json.loads(spacy_data)
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except JSONDecodeError as e:
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st.warning(f"Invalid JSON data, try again\n{str(e)}")
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else:
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run_data = demo_option
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if run_data:
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st.write("Spacy input data:")
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st.json(run_data)
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hf_data = spacy_to_hf(run_data, tok)
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df = Dataset.from_dict(hf_data).to_pandas()
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st.write("Output huggingface format:")
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st.dataframe(df)
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requirements.txt
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streamlit
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spacy-to-hf
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datasets
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