Update model to use doubly-tuned DGPT on Gab then MultiCONAN

app.py

@@ -1,12 +1,12 @@
 from response_generation import ResponseGenerator
 import gradio as gr
 
-DEFAULT_MODEL = "shaneweisz/DialoGPT-finetuned-multiCONAN"
+DEFAULT_MODEL = "shaneweisz/DialoGPT-finetuned-gab-multiCONAN"
 DECODING_CONFIG = {"max_new_tokens": 100, "min_new_tokens": 20, "no_repeat_ngram_size": 5, "num_beams": 10}
 
 TITLE = "Automating Counterspeech in Dialogue Systems"
 DESCRIPTION = """
-Built by [Shane Weisz](https://shaneweisz.com) for my research project on _Automating Counterspeech in Dialogue Systems_ as part of the [MPhil in Machine Learning and Machine Intelligence](https://www.mlmi.eng.cam.ac.uk/) at Cambridge University.
+This system has been built by [Shane Weisz](https://shaneweisz.com) for his research project on _Automating Counterspeech in Dialogue Systems_ as part of the [MPhil in Machine Learning and Machine Intelligence](https://www.mlmi.eng.cam.ac.uk/) at Cambridge University.
 <br/>
 The project is supervised by [Dr Marcus Tomalin](https://www.crassh.cam.ac.uk/about/people/marcus-tomalin/) and forms part of the [Giving Voice to Digital Democracies](https://www.crassh.cam.ac.uk/research/projects-centres/giving-voice-to-digital-democracies/) project on the _The Social Impact of Artificially Intelligent Communications Technology_.
 <br/>
@@ -30,5 +30,5 @@ model = ResponseGenerator(DEFAULT_MODEL, DECODING_CONFIG)
 def respond(input):
     return model.respond(input)
 
-demo = gr.Interface(fn=respond, inputs="text", outputs="text", examples=["Muslims are all terrorists", "Jews are selfish and greedy", "Why waste time listening to black women?"], cache_examples = False, title = TITLE, description = DESCRIPTION, article = ARTICLE)
+demo = gr.Interface(fn=respond, inputs="text", outputs="text", examples=["Muslims are all terrorists", "Jews are born greedy", "I'm tired of woman taking part in political debate. Feminism is a divisive force in society."], cache_examples = False, title = TITLE, description = DESCRIPTION, article = ARTICLE)
 demo.launch()