Synchronisation Production

README.md

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+---
+title: SAE-GPT2
+emoji: ❤️
+colorFrom: indigo
+colorTo: red
+sdk: gradio
+sdk_version: 3.50.2
+app_file: app.py
+pinned: false
+---
+
+<hr/>
+
+<h4> Environnement de développement commun </h4>
+
+<br/>
+
+| Nom        | Lien                                                  |
+|------------|-------------------------------------------------------|
+| Production | https://huggingface.co/spaces/FFatih/SAE-GPT2-PROD    |
+| Recette    | https://huggingface.co/spaces/FFatih/SAE-GPT2-RECETTE |
+
+<hr/>
+
+<h4> Environnement de développement personnel </h4>
+
+<br/>
+
+| Prenom            | Lien                                                       |
+|-------------------|------------------------------------------------------------|
+| Fatih             | https://huggingface.co/spaces/FFatih/SAE-GPT2-FATIH        |
+| Bastien           | https://huggingface.co/spaces/BastienHot/SAE-GPT2-BASTIEN  |
+| Pascal            | https://huggingface.co/spaces/PascalZhan/SAE-GPT2-PASCAL   |
+| Tamij             | https://huggingface.co/spaces/Tamij/SAE-GPT2-TAMIJ         |
+| Kevin             | https://huggingface.co/spaces/Kemasu/SAE-GPT2-KEVIN        |
+| Lilian            | https://huggingface.co/spaces/Solialiranes/SAE-GPT2-LILIAN |
+| Evan              | https://huggingface.co/spaces/Evanparis240/SAE-GPT2-EVAN   |

app.py

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+import gradio as gr
+
+def greet(name):
+    return "Hello " + name + "!!"
+
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface.launch()

gradio.py

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+# -*- coding: utf-8 -*-
+"""Untitled3.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1zwLQmMKCQKLMkJ_5Un4C6V4ajs4LYUOR
+"""
+"""
+!pip install --upgrade typing-extensions -q
+!pip install -q gradio --upgrade -q
+!pip install keras_nlp -q
+"""
+from google.colab import drive
+drive.mount('/content/drive')
+
+import os
+from tensorflow import keras
+import keras_nlp
+import gradio as gr
+import random
+import time
+
+os.environ["KERAS_BACKEND"] = "tensorflow"  # or "tensorflow" or "torch"
+keras.mixed_precision.set_global_policy("mixed_float16")
+
+preprocessor = keras_nlp.models.GPT2CausalLMPreprocessor.from_preset(
+    "gpt2_large_en",
+    sequence_length=256,
+)
+gpt2_lm = keras_nlp.models.GPT2CausalLM.from_preset(
+    "gpt2_large_en", preprocessor=preprocessor
+)
+
+gpt2_lm.load_weights('./drive/MyDrive/checkpoints/my_checkpoint')
+
+css = """
+.gradio-container {
+    background-color: transparent;
+    color: #f5f5dc;
+    border-color: #d5aa5e;
+}
+/* Styling for the chatbot  */
+.chat{
+    border-color: #d5aa5e;
+    background-color:#22201f;
+    background-image: url('https://github.com/BastienHot/SAE-GPT2/blob/70fb88500a2cc168d71e8ed635fc54492beb6241/image/logo.png');
+    background-size: cover;
+    background-position: center;
+}
+
+/* Styling for the user */
+.user{
+    background-color: #957d52;
+}
+
+/* Styling for the text inside the chatbot */
+.gradio-chatbox .message-container .message-right {
+    color: #f5f5dc; /* Antique white text color */
+    border-color: #d5aa5e;
+    background-color: red;
+}
+
+.md svelte-1syupzx chatbot{
+  border-color: #d5aa5e;
+    background-color: #3e3836;
+}
+
+.message user svelte-1lcyrx4 message-bubble-border {
+  border-color: #3e3836;
+}
+
+
+"""
+
+def predict(text):
+    # Simulating model prediction
+    return gpt2_lm.generate(text)
+
+with gr.Blocks(css=css) as demo:
+    chatbot = gr.Chatbot(elem_classes="chat")
+    msg = gr.Textbox(elem_classes="user")
+    clear = gr.ClearButton([msg, chatbot])
+
+    def respond(message, chat_history):
+        bot_message = predict(message)
+        # Ajouter une classe pour la partie bot_message
+        bot_message_html = f'<div class="bot-message">{bot_message}</div>'
+        # Ajouter une classe pour la partie message
+        user_message_html = f'<div class="user-message">{message}</div>'
+        chat_history.append((user_message_html, bot_message_html))
+        time.sleep(2)
+        return "", chat_history
+
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+
+
+if __name__ == "__main__":
+    demo.launch(debug=True, share=True)
+

requirements.txt

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+gradio
+keras_nlp
+typing-extensions