luelhagos
commited on
Commit
Β·
96c86c7
1
Parent(s):
61b42f7
initial
Browse files- app.py +95 -0
- requirements.txt +2 -0
app.py
ADDED
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import gradio as gr
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from transformers import pipeline, GPT2TokenizerFast
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modelId = "luel/gpt2-tigrinya-small"
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print("Loading tokenizer...")
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tokenizer = GPT2TokenizerFast.from_pretrained(modelId, model_max_length=128)
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print("Tokenizer loaded.")
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print("Loading model...")
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generator = pipeline("text-generation", model=modelId, tokenizer=tokenizer, pad_token_id=tokenizer.pad_token_id, eos_token_id=tokenizer.eos_token_id)
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print("Model loaded.")
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def generate_text(prompt, max_length, temperature):
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try:
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generated = generator(
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prompt,
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max_length=max_length,
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temperature=temperature,
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do_sample=True,
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repetition_penalty=1.5
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)
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return generated[0]['generated_text']
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except Exception as e:
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return f"Something went wrong, try again. Error: {str(e)}"
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def create_interface():
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with gr.Blocks() as demo:
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gr.Markdown("# Tigrinya Text Generator (GPT-2)")
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gr.Markdown(
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"This is a GPT-2 model trained from scratch on Tigrinya text data, primarily from news sources. "
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"Enter your Tigrinya text prompt and adjust the parameters to generate text."
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)
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with gr.Row():
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input_temperature = gr.Slider(
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minimum=0.1,
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maximum=1.0,
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value=0.7,
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step=0.1,
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label="Temperature",
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)
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input_max_length = gr.Slider(
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minimum=10,
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maximum=128,
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value=60,
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step=1,
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label="Maximum Length",
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)
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with gr.Row():
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with gr.Column(scale=1):
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input_prompt = gr.Textbox(
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label="Enter your Tigrinya text prompt",
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placeholder="α΅αα«α",
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lines=5
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)
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with gr.Column(scale=1):
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output_text = gr.Textbox(
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label="Generated Text",
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lines=5,
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interactive=True
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)
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with gr.Row():
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generate_btn = gr.Button("Generate", variant="primary")
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clear_btn = gr.Button("Clear")
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generate_btn.click(
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fn=generate_text,
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inputs=[input_prompt, input_max_length, input_temperature],
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outputs=output_text
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)
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clear_btn.click(
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fn=lambda: ("", ""),
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inputs=[],
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outputs=[input_prompt, output_text]
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)
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gr.Examples(
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examples=[
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["α΅αα«α"],
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["α£α²α΅ α£α α£"],
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["α°αα"]
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],
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inputs=input_prompt
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)
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return demo
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if __name__ == "__main__":
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demo = create_interface()
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demo.queue().launch(debug=True)
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requirements.txt
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transformers==4.46.0
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torch==2.5.0
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