Spaces:
Running
on
Zero
Running
on
Zero
Commit
•
cce4feb
1
Parent(s):
496bd7a
Added news title generation
Browse files
app.py
CHANGED
@@ -109,6 +109,14 @@ def summarize(input, model_choice, max_new_tokens, length_penalty, no_repeat_ngr
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summarization_model = pipeline(model=model_mapping[model_choice], device=0)
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return summarization_model(input, max_new_tokens = max_new_tokens, length_penalty=length_penalty, no_repeat_ngram_size=no_repeat_ngram_size)[0]["generated_text"]
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@spaces.GPU
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def categorize(input):
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ttc = pipeline(model="boun-tabi-LMG/turna_classification_ttc4900", device=0)
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@@ -241,6 +249,30 @@ with gr.Blocks(theme="abidlabs/Lime") as demo:
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sum_submit.click(summarize, inputs=[sum_input, sum_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=sum_output)
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sum_examples = gr.Examples(examples = long_text, inputs = [sum_input, sum_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=sum_output, fn=summarize)
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with gr.Tab("Text Generation"):
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gr.Markdown("Pre-trained TURNA. Enter text to start generating.")
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with gr.Column():
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summarization_model = pipeline(model=model_mapping[model_choice], device=0)
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return summarization_model(input, max_new_tokens = max_new_tokens, length_penalty=length_penalty, no_repeat_ngram_size=no_repeat_ngram_size)[0]["generated_text"]
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@spaces.GPU
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def generate_title(input, model_choice, max_new_tokens, length_penalty, no_repeat_ngram_size):
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model_mapping = {"turna_title_generation_tr_news": "boun-tabi-LMG/turna_title_generation_tr_news",
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"turna_title_generation_mlsum": "boun-tabi-LMG/turna_title_generation_mlsum"}
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summarization_model = pipeline(model=model_mapping[model_choice], device=0)
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return summarization_model(input, max_new_tokens = max_new_tokens, length_penalty=length_penalty, no_repeat_ngram_size=no_repeat_ngram_size)[0]["generated_text"]
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@spaces.GPU
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def categorize(input):
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ttc = pipeline(model="boun-tabi-LMG/turna_classification_ttc4900", device=0)
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sum_submit.click(summarize, inputs=[sum_input, sum_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=sum_output)
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sum_examples = gr.Examples(examples = long_text, inputs = [sum_input, sum_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=sum_output, fn=summarize)
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with gr.Tab("Title Generation"):
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gr.Markdown("TURNA fine-tuned on news title generation. Enter news text to generate a title.")
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with gr.Column():
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with gr.Row():
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with gr.Column():
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title_choice = gr.Radio(choices = ["turna_title_generation_tr_news", "turna_title_generation_mlsum"], label ="Model", value="turna_title_generation_tr_news")
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with gr.Accordion("Advanced Generation Parameters"):
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max_new_tokens = gr.Slider(label = "Maximum length",
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minimum = 0,
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maximum = 64,
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value = 64)
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length_penalty = gr.Slider(label = "Length penalty",
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minimum = -10,
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maximum = 10,
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value=2.0)
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no_repeat_ngram_size =gr.Slider(label="No Repeat N-Gram Size", minimum=0,value=3,)
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with gr.Column():
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title_input = gr.Textbox(label = "News Title Generation Input")
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title_submit = gr.Button()
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title_output = gr.Textbox(label = "News Title Generation Output")
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title_submit.click(generate_title, inputs=[title_input, title_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=title_output)
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title_examples = gr.Examples(examples = long_text, inputs = [title_input, title_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=title_output, fn=generate_title)
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with gr.Tab("Text Generation"):
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gr.Markdown("Pre-trained TURNA. Enter text to start generating.")
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with gr.Column():
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