initial

app.py

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+import gradio as gr
+from transformers import pipeline, GPT2TokenizerFast
+
+modelId = "luel/gpt2-tigrinya-small"
+
+print("Loading tokenizer...")
+tokenizer = GPT2TokenizerFast.from_pretrained(modelId, model_max_length=128)
+print("Tokenizer loaded.")
+
+print("Loading model...")
+generator = pipeline("text-generation", model=modelId, tokenizer=tokenizer, pad_token_id=tokenizer.pad_token_id, eos_token_id=tokenizer.eos_token_id)
+print("Model loaded.")
+
+def generate_text(prompt, max_length, temperature):
+    try:
+        generated = generator(
+            prompt,
+            max_length=max_length,
+            temperature=temperature,
+            do_sample=True,
+            repetition_penalty=1.5
+        )
+        return generated[0]['generated_text']
+    except Exception as e:
+        return f"Something went wrong, try again. Error: {str(e)}"
+
+def create_interface():
+    with gr.Blocks() as demo:
+        gr.Markdown("# Tigrinya Text Generator (GPT-2)")
+        gr.Markdown(
+            "This is a GPT-2 model trained from scratch on Tigrinya text data, primarily from news sources. "
+            "Enter your Tigrinya text prompt and adjust the parameters to generate text."
+        )
+        
+        with gr.Row():
+            input_temperature = gr.Slider(
+                minimum=0.1,
+                maximum=1.0,
+                value=0.7,
+                step=0.1,
+                label="Temperature",
+            )
+            input_max_length = gr.Slider(
+                minimum=10,
+                maximum=128,
+                value=60,
+                step=1,
+                label="Maximum Length",
+            )
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                input_prompt = gr.Textbox(
+                    label="Enter your Tigrinya text prompt",
+                    placeholder="ትግራይ",
+                    lines=5
+                )
+            
+            with gr.Column(scale=1):
+                output_text = gr.Textbox(
+                    label="Generated Text",
+                    lines=5,
+                    interactive=True
+                )
+        
+        with gr.Row():
+            generate_btn = gr.Button("Generate", variant="primary")
+            clear_btn = gr.Button("Clear")
+        
+        generate_btn.click(
+            fn=generate_text,
+            inputs=[input_prompt, input_max_length, input_temperature],
+            outputs=output_text
+        )
+        
+        clear_btn.click(
+            fn=lambda: ("", ""),
+            inputs=[],
+            outputs=[input_prompt, output_text]
+        )
+        
+        gr.Examples(
+            examples=[
+                ["ትግራይ"],
+                ["ኣዲስ ኣበባ"],
+                ["ሰላም"]
+            ],
+            inputs=input_prompt
+        )
+    
+    return demo            
+
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.queue().launch(debug=True)

requirements.txt

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+transformers==4.46.0
+torch==2.5.0