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| import gradio as gr | |
| import numpy as np | |
| import pandas as pd | |
| import re | |
| import shap | |
| from transformers import ( | |
| AutoTokenizer, | |
| AutoModelForSequenceClassification, | |
| TextClassificationPipeline, | |
| ) | |
| tokenizer = AutoTokenizer.from_pretrained("chinhon/fake_tweet_detect") | |
| model = AutoModelForSequenceClassification.from_pretrained("chinhon/fake_tweet_detect") | |
| tweet_detector = TextClassificationPipeline(model=model, tokenizer=tokenizer) | |
| # tweak the extent of text cleaning as you wish | |
| def clean_text(text): | |
| text = re.sub(r"http\S+", "", text) | |
| text = re.sub(r"\n", " ", text) | |
| text = re.sub(r"\'t", " not", text) # Change 't to 'not' | |
| text = re.sub(r"(@.*?)[\s]", " ", text) # Remove @name | |
| text = re.sub(r"$\d+\W+|\b\d+\b|\W+\d+$", " ", text) # remove digits | |
| text = re.sub(r"[^\w\s\#]", "", text) # remove special characters except hashtags | |
| text = text.strip(" ") | |
| text = re.sub( | |
| " +", " ", text | |
| ).strip() # get rid of multiple spaces and replace with a single | |
| return text | |
| def tweet_detect(text): | |
| data = [clean_text(text)] | |
| prediction = tweet_detector(data) | |
| pred_label = [x.get("label") for x in prediction] | |
| if pred_label == ["LABEL_1"]: | |
| return "Fake Tweet" | |
| elif pred_label == ["LABEL_0"]: | |
| return "Real Tweet" | |
| #Define Gradio interface | |
| gradio_ui = gr.Interface( | |
| fn=tweet_detect, | |
| title="Detect Fake Tweets", | |
| description="Enter a tweet and see if a Distilbert model can identify if it was written by state-backed trolls. DISCLAIMER: While the model was fine tuned on 100k real and troll tweets, and achieved high accuracy in my tests, its performance drops significantly against the day-to-day barrage of content on Twitter. As such, this app is intended as an example for understanding the limits of AI/ML in highly complex problems like fake media detection, and not as a final arbiter of whether someone's tweet is real or not.", | |
| inputs=gr.Textbox(lines=10, label="Paste tweet text here [English Only]"), | |
| outputs=gr.Label(type="auto", label="Prediction"), | |
| interpretation="shap", | |
| article="Details of the fine tuning and tests are in this Medium post: https://bit.ly/3tueP36", | |
| ) | |
| gradio_ui.launch(enable_queue=True) | |