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| import gradio as gr | |
| # Assuming we have a function to load a tokenizer by name (you would need to replace this with actual implementation) | |
| def load_tokenizer(tokenizer_name): | |
| if tokenizer_name == "aranizer_sp32k": | |
| tokenizer = aranizer_sp32k.get_tokenizer() | |
| # Add conditions for other tokenizers | |
| return tokenizer | |
| def tokenize_and_encode(text, tokenizer_choice): | |
| tokenizer = load_tokenizer(tokenizer_choice) | |
| tokens = tokenizer.tokenize(text) | |
| encoded_output = tokenizer.encode(text, add_special_tokens=True) | |
| decoded_text = tokenizer.decode(encoded_output) | |
| return tokens, encoded_output, decoded_text | |
| iface = gr.Interface( | |
| fn=tokenize_and_encode, | |
| inputs=[gr.inputs.Textbox(lines=5, label="النص العربي"), gr.inputs.Dropdown(choices=["aranizer_bpe32k", "aranizer_bpe50k", "aranizer_bpe64k", "aranizer_bpe86k", "aranizer_sp32k", "aranizer_sp50k", "aranizer_sp64k", "aranizer_sp86k"], label="اختر المحلل اللفظي")], | |
| outputs=[gr.outputs.Textbox(label="Tokens"), gr.outputs.Textbox(label="Encoded Output"), gr.outputs.Textbox(label="Decoded Text")], | |
| title="مقارنة المحللات اللفظية للنص العربي", | |
| description="حدد نوع المحلل اللفظي وأدخل نصًا لرؤية النتائج.", | |
| language="ar", | |
| ) | |
| iface.launch() |