Upload app

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+
+# Define the function to handle text generation
+def generate_text(model_name, text, num_beams, max_length, top_p, temperature, repetition_penalty, no_repeat_ngram_size):
+    # Load tokenizer and model
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+    
+    # Initialize pipeline
+    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+    
+    # Generate text with the specified parameters
+    generated_text = pipe(text,
+                          pad_token_id=tokenizer.eos_token_id,
+                          num_beams=num_beams,
+                          max_length=max_length,
+                          top_p=top_p,
+                          temperature=temperature,
+                          repetition_penalty=repetition_penalty,
+                          no_repeat_ngram_size=no_repeat_ngram_size)[0]['generated_text']
+    
+    return generated_text
+
+# Define model options
+model_options = [
+    "riotu-lab/ArabianGPT-01B",
+    "riotu-lab/ArabianGPT-03B",
+    "riotu-lab/ArabianGPT-08B"
+]
+
+# Define Gradio interface components
+inputs_component = [
+    gr.Dropdown(choices=model_options, label="Select Model"),
+    gr.Textbox(lines=2, placeholder="Enter your text here...", label="Input Text"),
+    gr.Slider(minimum=1, maximum=10, step=1, default=5, label="Num Beams"),
+    gr.Slider(minimum=50, maximum=300, step=10, default=200, label="Max Length"),
+    gr.Slider(minimum=0.0, maximum=1.0, step=0.1, default=0.9, label="Top p"),
+    gr.Slider(minimum=0.0, maximum=1.0, step=0.1, default=0.1, label="Temperature"),
+    gr.Slider(minimum=1.0, maximum=5.0, step=0.5, default=3.0, label="Repetition Penalty"),
+    gr.Slider(minimum=2, maximum=5, step=1, default=3, label="No Repeat Ngram Size")
+]
+
+# Setup the interface
+iface = gr.Interface(
+    fn=generate_text,
+    inputs=inputs_component,
+    outputs="text",
+    title="ArabianGPT Playground",
+    description="Explore the capabilities of ArabianGPT models. Adjust the hyperparameters to see how they affect text generation.",
+    live=True
+)
+
+# Launch the app
+iface.launch()