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Taranosaurus
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54d4ac0
1
Parent(s):
1619049
Added hypothesis_template and removed superfluous tokenizer
Browse filesThe hypothesis_template can be used to make the labelling more malleable give better classifications from the input text
app.py
CHANGED
@@ -1,4 +1,4 @@
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from transformers import pipeline
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import gradio as gr
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import torch
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@@ -9,17 +9,17 @@ else:
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summary_checkpoint = "facebook/bart-large-cnn" #"google/pegasus-large"
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oracle_checkpoint = "facebook/bart-large-mnli"
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summary = pipeline(task="summarization", model=summary_checkpoint, tokenizer=tokenizer, device=device)
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oracle = pipeline(task="zero-shot-classification", model=oracle_checkpoint, device=device)
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labels = ["merge","revert","fix","feature","update","refactor","test","security","documentation","style"]
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selected_labels = ["feature","update","refactor","test","security","documentation","style"]
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def do_the_thing(input, labels):
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summarisation = summary(input, truncation=True)[0]['summary_text']
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zsc_results = oracle(sequences=[input, summarisation], candidate_labels=labels, multi_label=False, batch_size=2)
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classifications_input = {}
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for i in range(len(labels)):
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classifications_input.update({zsc_results[0]['labels'][i]: zsc_results[0]['scores'][i]})
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@@ -37,6 +37,7 @@ with gr.Blocks() as frontend:
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with gr.Row():
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with gr.Column():
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input_labels = gr.Dropdown(label="Classification Labels", choices=labels, multiselect=True, value=selected_labels, interactive=True, allow_custom_value=True, info="Labels to classify the original text and summary")
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with gr.Column():
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output_summary_text = gr.TextArea(label="Summary of Notes")
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with gr.Row():
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@@ -44,6 +45,6 @@ with gr.Blocks() as frontend:
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output_original_labels = gr.Label(label="Original Text Classification")
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with gr.Column():
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output_summary_labels = gr.Label(label="Summary Text Classification")
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btn_submit.click(fn=do_the_thing, inputs=[input_value, input_labels], outputs=[output_summary_text, output_original_labels, output_summary_labels])
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frontend.launch()
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from transformers import pipeline
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import gradio as gr
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import torch
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summary_checkpoint = "facebook/bart-large-cnn" #"google/pegasus-large"
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oracle_checkpoint = "facebook/bart-large-mnli"
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summary = pipeline(task="summarization", model=summary_checkpoint, device=device)
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oracle = pipeline(task="zero-shot-classification", model=oracle_checkpoint, device=device)
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labels = ["merge","revert","fix","feature","update","refactor","test","security","documentation","style"]
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selected_labels = ["feature","update","refactor","test","security","documentation","style"]
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def do_the_thing(input, hypothesis, labels):
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if hypothesis == None or hypothesis == "" or '{}' not in hypothesis:
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hypothesis= "This example is {}."
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summarisation = summary(input, truncation=True)[0]['summary_text']
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zsc_results = oracle(sequences=[input, summarisation], candidate_labels=labels, multi_label=False, batch_size=2, hypothesis_template=hypothesis)
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classifications_input = {}
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for i in range(len(labels)):
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classifications_input.update({zsc_results[0]['labels'][i]: zsc_results[0]['scores'][i]})
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with gr.Row():
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with gr.Column():
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input_labels = gr.Dropdown(label="Classification Labels", choices=labels, multiselect=True, value=selected_labels, interactive=True, allow_custom_value=True, info="Labels to classify the original text and summary")
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input_hypothesis = gr.Textbox(label="Hypothesis Template", info="This must include the {} format syntax. Blank and invalid inputs get defaulted to the palceholder text.", value="This git commit relates to {} changes.", placeholder="This example is {}.")
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with gr.Column():
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output_summary_text = gr.TextArea(label="Summary of Notes")
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with gr.Row():
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output_original_labels = gr.Label(label="Original Text Classification")
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with gr.Column():
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output_summary_labels = gr.Label(label="Summary Text Classification")
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btn_submit.click(fn=do_the_thing, inputs=[input_value, input_hypothesis, input_labels], outputs=[output_summary_text, output_original_labels, output_summary_labels])
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frontend.launch()
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