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AIChatAssistantPhi2

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Sijuade commited on Dec 19, 2023

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87d9314

1 Parent(s): f59792e

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app.py +45 -0
requirements.txt +6 -0
utils.py +181 -0

app.py ADDED Viewed

	@@ -0,0 +1,45 @@

+import gradio as gr
+import random
+import torch
+from utils import *
+with gr.Blocks() as demo:
+  with gr.Row():
+    show_label = True
+    gr.HTML(value=generate_html, show_label=show_label)
+  with gr.Row():
+    temp = gr.Slider(0, 1, value=0.2, label="Temperature", info="Choose between 0 and 1")
+    seed = gr.Slider(0, 1000, value=42, label="Seed", info="Select Random Seed")
+    max_tokens = gr.Slider(100, 1000, value=200, label="Max Tokens", info="Choose Max Tokens")
+  with gr.Row():
+    with gr.Column():
+      chatbot = gr.Chatbot()
+      msg = gr.Textbox(label='Message AI Assistant')
+      clear = gr.ClearButton([msg, chatbot])
+    def respond(message, chat_history, temp, seed, max_tokens):
+        torch.manual_seed(seed)
+        model_inputs = tokenizer(
+                    [f"[INST] {message} [/INST]"],
+                    return_tensors="pt", padding=True)
+        generated_ids = model.generate(**model_inputs, max_new_tokens=max_tokens)
+        result = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
+        bot_message = extract_responses(result[0])
+        chat_history.append((message, bot_message))
+        return "", chat_history
+    msg.submit(respond, [msg, chatbot, temp, seed, max_tokens], [msg, chatbot])
+  with gr.Row():
+    show_label = True
+    gr.HTML(value=generate_footer, show_label=show_label)
+if __name__ == "__main__":
+    demo.launch()

requirements.txt ADDED Viewed

	@@ -0,0 +1,6 @@

+torch
+transformers
+einops
+git+https://github.com/huggingface/peft.git
+accelerate
+gradio

utils.py ADDED Viewed

	@@ -0,0 +1,181 @@

+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+def extract_responses(text):
+    """
+    Extracts and returns the responses from the text, excluding the parts
+    between and including the [INST] tags.
+    Args:
+    text (str): The input text containing responses and [INST] tags.
+    Returns:
+    str: The extracted responses.
+    """
+    import re
+    # Split the text by [INST] tags and accumulate non-tag parts
+    parts = re.split(r'\[INST\].*?\[/INST\]', text, flags=re.DOTALL)
+    cleaned_text = "".join(parts)
+    # Return the cleaned and trimmed text
+    return cleaned_text.strip()
+def generate_html():
+  return(
+      '''
+    <!DOCTYPE html>
+    <html lang="en">
+    <head>
+        <meta charset="UTF-8">
+        <meta name="viewport" content="width=device-width, initial-scale=1.0">
+        <title>Your Gradio App</title>
+        <style>
+            @import url('https://fonts.googleapis.com/css2?family=Montserrat:wght@300;400&display=swap');
+            body, html {
+                margin: 0;
+                padding: 0;
+                font-family: 'Montserrat', sans-serif;
+                background: #f9f9f9;
+            }
+            header {
+                background-color: #e8f0fe;
+                color: #333;
+                text-align: center;
+                padding: 40px 20px;
+                border-radius: 0 0 25px 25px;
+                background-image: linear-gradient(to right, #a7c7e7, #c0d8f0);
+                box-shadow: 0 8px 16px 0 rgba(0,0,0,0.2);
+                position: relative;
+                overflow: hidden;
+            }
+            .background-shapes {
+                position: absolute;
+                top: 0;
+                left: 0;
+                right: 0;
+                bottom: 0;
+                background-image: linear-gradient(120deg, #a7c7e7 0%, #c0d8f0 100%);
+                opacity: 0.6;
+                animation: pulse 5s ease-in-out infinite alternate;
+            }
+            .header-content h1 {
+                font-size: 2.8em;
+                margin: 0;
+            }
+            .header-content p {
+                font-size: 1.3em;
+                margin-top: 20px;
+            }
+            @keyframes pulse {
+                from { background-size: 100% 100%; }
+                to { background-size: 110% 110%; }
+            }
+        </style>
+    </head>
+    <body>
+        <header>
+            <div class="background-shapes"></div>
+            <div class="header-content">
+                <h1>AI Assistant</h1>
+                <p>This interactive app leverages the power of a fine-tuned Phi 2 AI model to provide insightful responses. Type your query below and witness AI in action.</p>
+            </div>
+        </header>
+        <!-- Rest of your Gradio app goes here -->
+    </body>
+    </html>
+  ''')
+def generate_footer():
+  return(
+      '''
+    <!DOCTYPE html>
+    <html lang="en">
+    <head>
+        <meta charset="UTF-8">
+        <meta name="viewport" content="width=device-width, initial-scale=1.0">
+        <title>Your Gradio App</title>
+        <style>
+            @import url('https://fonts.googleapis.com/css2?family=Roboto+Slab:wght@400;700&display=swap');
+            body, html {
+                margin: 0;
+                padding: 0;
+                font-family: 'Roboto Slab', serif;
+                background: #f9f9f9;
+            }
+            header, footer {
+                color: #333;
+                text-align: center;
+                padding: 40px 20px;
+                border-radius: 25px;
+                background: linear-gradient(120deg, #a7c7e7 0%, #c0d8f0 100%);
+                background-size: 200% 200%;
+                animation: gradientShift 8s ease-in-out infinite;
+                position: relative;
+                overflow: hidden;
+            }
+            .header-content, .footer-content {
+                position: relative;
+                z-index: 1;
+            }
+            .header-content h1, .footer-content p {
+                font-size: 2.8em;
+                margin: 0;
+            }
+            .header-content p, .footer-content p {
+                font-size: 1.3em;
+                margin-top: 20px;
+            }
+            @keyframes gradientShift {
+                0% { background-position: 0% 50%; }
+                50% { background-position: 100% 50%; }
+                100% { background-position: 0% 50%; }
+            }
+            footer {
+                margin-top: 40px;
+                border-radius: 25px 25px 0 0;
+            }
+        </style>
+    </head>
+    <body>
+        <footer>
+            <div class="footer-content">
+                <p>This model was fine-tuned on a subset of the OpenAssistant dataset.</p>
+            </div>
+        </footer>
+    </body>
+    </html>
+  ''')
+model = AutoModelForCausalLM.from_pretrained(
+    "microsoft/phi-2",
+    torch_dtype=torch.float32,
+    device_map="cpu",
+    trust_remote_code=True
+)
+model.load_adapter('checkpoint-780')
+tokenizer = AutoTokenizer.from_pretrained('checkpoint-780', trust_remote_code=True)
+tokenizer.pad_token = tokenizer.eos_token