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#!/usr/bin/env python | |
# coding: utf-8 | |
# ### Keywords to Title Generator | |
# - https://huggingface.co/EnglishVoice/t5-base-keywords-to-headline?text=diabetic+diet+plan | |
# - Apache 2.0 | |
# In[7]: | |
import torch | |
from transformers import T5ForConditionalGeneration,T5Tokenizer | |
device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
model = T5ForConditionalGeneration.from_pretrained("EnglishVoice/t5-base-keywords-to-headline") | |
tokenizer = T5Tokenizer.from_pretrained("EnglishVoice/t5-base-keywords-to-headline", clean_up_tokenization_spaces=True, legacy=False) | |
model = model.to(device) | |
# In[37]: | |
def title_gen(keywords, diversity, temp): | |
if keywords!= "": | |
text = "headline: " + keywords | |
encoding = tokenizer.encode_plus(text, return_tensors = "pt") | |
input_ids = encoding["input_ids"].to(device) | |
attention_masks = encoding["attention_mask"].to(device) | |
if diversity: | |
num_beams = 20, | |
num_beam_groups = 20, | |
diversity_penalty=0.8, | |
early_stopping = True, | |
else: | |
penalty_alpha = 0.8, | |
beam_outputs = model.generate( | |
input_ids = input_ids, | |
attention_mask = attention_masks, | |
max_new_tokens = 30, | |
do_sample = True, | |
num_return_sequences = 5, | |
temperature = temp, | |
top_k = 15, | |
no_repeat_ngram_size = 3, | |
#top_p = 0.60, | |
) | |
titles = "" | |
for i in range(len(beam_outputs)): | |
result = tokenizer.decode(beam_outputs[i], skip_special_tokens=True) | |
titles += f"<p align=center><b>{result}</b></p>" #Create string with titles and <br> tag for html reading in gradio html | |
return titles | |
# In[8]: | |
import gradio as gr | |
# In[40]: | |
iface = gr.Interface(fn=title_gen, | |
inputs=[gr.Textbox(label="Paste one or more keywords searated by a comma and hit 'Submit'.", lines=1), "checkbox", gr.Slider(0.1, 1.9, 1.2)], | |
outputs=[gr.HTML(label="Title suggestions:")], | |
title="AI Keywords to Title Generator", | |
#description="Turn keywords into creative suggestions", | |
article="<div align=left><h1>AI Creative Title Generator</h1><li>With just keywords, generate a list of creative titles.</li><li>Click on Submit to generate more title options.</li><li>Tweak slider for less or more creative titles</li><li>Check 'diversity' to turn on diversity beam search</li><p>AI Model:<br><li>T5 Model trained on a dataset of titles and related keywords</li><li>Original model id: EnglishVoice/t5-base-keywords-to-headline by English Voice AI Labs</li></p><p>Default parameter details:<br><li>Temperature = 1.2, no_repeat_ngram_size=3, top_k = 15, penalty_alpha = 0.8, max_new_tokens = 30</li><p>Diversity beam search params:<br><li>num_beams=20, diversity_penalty=0.8, num_beam_groups=20</li></div>", | |
flagging_mode='never' | |
) | |
iface.launch() | |
# In[ ]: | |
''' | |
#Create a four button panel for changing parameters with one click | |
def fn(text): | |
return ("Hello gradio!") | |
with gr.Blocks () as demo: | |
with gr.Row(variant='compact') as PanelRow1: #first row: top | |
with gr.Column(scale=0, min_width=180) as PanelCol5: | |
gr.HTML("") | |
with gr.Column(scale=0) as PanelCol4: | |
submit = gr.Button("Temp++", scale=0) | |
with gr.Column(scale=1) as PanelCol5: | |
gr.HTML("") | |
with gr.Row(variant='compact') as PanelRow2: #2nd row: left, right, middle | |
with gr.Column(min_width=100) as PanelCol1: | |
submit = gr.Button("Contrastive") | |
with gr.Column(min_width=100) as PanelCol2: | |
submit = gr.Button("Re-generate") | |
with gr.Column(min_width=100) as PanelCol3: | |
submit = gr.Button("Diversity Beam") | |
with gr.Column(min_width=100) as PanelCol5: | |
gr.HTML("") | |
with gr.Column(min_width=100) as PanelCol5: | |
gr.HTML("") | |
with gr.Column(scale=0) as PanelCol5: | |
gr.HTML("") | |
with gr.Row(variant='compact') as PanelRow3: #last row: down | |
with gr.Column(scale=0, min_width=180) as PanelCol7: | |
gr.HTML("") | |
with gr.Column(scale=1) as PanelCol6: | |
submit = gr.Button("Temp--", scale=0) | |
with gr.Column(scale=0) as PanelCol5: | |
gr.HTML("") | |
demo.launch() | |
''' | |