Create app3.py

app3.py

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+import gradio as gr
+from transformers import GPT2LMHeadModel, GPT2Tokenizer, TextDataset, DataCollatorForLanguageModeling, Trainer, TrainingArguments
+from datasets import load_dataset
+import numpy as np
+import torch
+
+# Load GPT2 Model and Tokenizer
+model_name = "gpt2"
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+model = GPT2LMHeadModel.from_pretrained(model_name)
+
+# Define PPO Training Function (simplified)
+def fine_tune_gpt2_with_ppo(dataset_name, epochs, learning_rate):
+    # Load the dataset
+    dataset = load_dataset(dataset_name)
+    
+    # Prepare dataset for GPT-2 training
+    def encode(examples):
+        return tokenizer(examples['text'], truncation=True, padding='max_length', max_length=128)
+
+    tokenized_dataset = dataset.map(encode, batched=True)
+    train_dataset = tokenized_dataset["train"]
+    
+    # Prepare data collator and training arguments
+    data_collator = DataCollatorForLanguageModeling(tokenizer=tokenizer, mlm=False)
+    training_args = TrainingArguments(
+        output_dir="./results",
+        overwrite_output_dir=True,
+        num_train_epochs=epochs,
+        per_device_train_batch_size=4,
+        save_steps=10_000,
+        save_total_limit=2,
+        learning_rate=learning_rate
+    )
+    
+    # Trainer
+    trainer = Trainer(
+        model=model,
+        args=training_args,
+        data_collator=data_collator,
+        train_dataset=train_dataset
+    )
+    
+    # Train model
+    trainer.train()
+    
+    return "Training Completed!"
+
+# Gradio Interface
+def train_interface(dataset, epochs, learning_rate):
+    result = fine_tune_gpt2_with_ppo(dataset, int(epochs), float(learning_rate))
+    return result
+
+# Gradio App
+gradio_interface = gr.Interface(
+    fn=train_interface,
+    inputs=[
+        gr.inputs.Textbox(label="Dataset (e.g. 'wikitext')"),
+        gr.inputs.Slider(1, 10, step=1, label="Epochs"),
+        gr.inputs.Textbox(label="Learning Rate")
+    ],
+    outputs="text",
+    title="GPT-2 RL Training App",
+    description="Fine-tune GPT-2 using PPO via a Gradio interface."
+)
+
+# Launch the app
+gradio_interface.launch()