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app.py

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+# -*- coding: utf-8 -*-
+"""chat.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1FxpG0gxd0Oigj5CAekXbdwgu7NdtI5sF
+"""
+
+!pip install -r requirements.txt
+
+from transformers import pipeline, Conversation
+import gradio as gr
+
+# toy example 1
+pipeline(task="sentiment-analysis")("Love this!")
+
+# toy example 2
+pipeline(task="sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")("Love this!")
+
+# defining classifier
+classifier = pipeline(task="sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
+
+classifier("Hate this.")
+
+# we can also pass in a list to classifier
+text_list = ["This is great", \
+             "Thanks for nothing", \
+             "You've got to work on your face", \
+             "You're beautiful, never change!"]
+
+classifier(text_list)
+
+# if there are multiple target labels, we can return them all
+classifier = pipeline(task="text-classification", model="SamLowe/roberta-base-go_emotions", top_k=None)
+
+classifier(text_list[0])
+
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+text = """
+Hugging Face is an AI company that has become a major hub for open-source machine learning.
+Their platform has 3 major elements which allow users to access and share machine learning resources.
+First, is their rapidly growing repository of pre-trained open-source machine learning models for things such as natural language processing (NLP), computer vision, and more.
+Second, is their library of datasets for training machine learning models for almost any task.
+Third, and finally, is Spaces which is a collection of open-source ML apps.
+
+The power of these resources is that they are community generated, which leverages all the benefits of open source i.e. cost-free, wide diversity of tools, high quality resources, and rapid pace of innovation.
+While these make building powerful ML projects more accessible than before, there is another key element of the Hugging Face ecosystem—their Transformers library.
+"""
+summarized_text = summarizer(text, min_length=5, max_length=140)[0]['summary_text']
+summarized_text
+
+classifier(summarized_text)
+
+chatbot = pipeline(model="facebook/blenderbot-400M-distill")
+
+conversation = chatbot("Hi I'm Shaw, how are you?")
+
+conversation
+
+conversation = chatbot("Where do you work?")
+
+conversation
+
+def top3_text_classes(message, history):
+    return str(classifier(message)[0][:3]).replace('}, {', '\n').replace('[{', '').replace('}]', '')
+
+demo_sentiment = gr.ChatInterface(top3_text_classes, title="Text Sentiment Chatbot", description="Enter your text, and the chatbot will classify the sentiment.")
+
+demo_sentiment.launch()
+
+def summarizer_bot(message, history):
+    return summarizer(message, min_length=5, max_length=140)[0]['summary_text']
+
+demo_summarizer = gr.ChatInterface(summarizer_bot, title="Summarizer Chatbot", description="Enter your text, and the chatbot will return the summarized version.")
+
+demo_summarizer.launch()
+
+message_list = []
+response_list = []
+
+def vanilla_chatbot(message, history):
+    conversation = chatbot(message)
+
+    return conversation[0]['generated_text']
+
+demo_chatbot = gr.ChatInterface(vanilla_chatbot, title="Vanilla Chatbot", description="Enter text to start chatting.")
+
+demo_chatbot.launch()

requirements.txt

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+accelerate==0.21.0
+certifi==2023.7.22
+filelock==3.12.2
+fsspec==2023.6.0
+gradio==3.39.0
+huggingface-hub==0.16.4
+mpmath==1.3.0
+networkx==3.1
+numpy==1.25.1
+pyyaml==6.0.1
+regex==2023.6.3
+safetensors==0.3.1
+sympy==1.12
+tokenizers==0.13.3
+torch==2.0.1
+tqdm==4.65.0
+transformers==4.31.0