Create app.py

app.py

@@ -0,0 +1,82 @@
+import gradio as gr
+from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
+import os
+
+# Define model paths
+MODEL_PATHS = {
+    "Terjman-Nano-v2": "BounharAbdelaziz/Terjman-Nano-v2.0",
+    "Terjman-Large-v2": "BounharAbdelaziz/Terjman-Large-v2.0",
+    "Terjman-Ultra-v2": "BounharAbdelaziz/Terjman-Ultra-v2.0",
+    "Terjman-Supreme-v2": "BounharAbdelaziz/Terjman-Supreme-v2.0"
+}
+
+
+# Translation function for Nano and Large models
+def translate_nano_large(text, model_path):
+    translator = pipeline("translation", model=model_path)
+    translated = translator(
+        text, 
+        max_length=512,
+        num_beams=4,
+        no_repeat_ngram_size=3,
+        early_stopping=True,
+        do_sample=False,
+        pad_token_id=translator.tokenizer.pad_token_id,
+        bos_token_id=translator.tokenizer.bos_token_id,
+        eos_token_id=translator.tokenizer.eos_token_id
+    )
+    return translated[0]["translation_text"]
+
+# Translation function for Ultra and Supreme models
+def translate_ultra_supreme(text, model_path):
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
+    tokenizer = AutoTokenizer.from_pretrained(model_path, src_lang="eng_Latn", tgt_lang="ary_Arab")
+    translator = pipeline(
+        "translation",
+        model=model,
+        tokenizer=tokenizer,
+        max_length=512,
+        src_lang="eng_Latn",
+        tgt_lang="ary_Arab"
+    )
+    translation = translator(text)[0]['translation_text']
+    return translation
+
+# Main translation function
+def translate_text(text, model_choice):
+    model_path = MODEL_PATHS[model_choice]
+    if model_choice in ["Terjman-Nano-v2", "Terjman-Large-v2"]:
+        return translate_nano_large(text, model_path)
+    elif model_choice in ["Terjman-Ultra-v2", "Terjman-Supreme-v2"]:
+        return translate_ultra_supreme(text, model_path)
+    else:
+        return "Invalid model selection."
+
+# Gradio app
+def gradio_app():
+    with gr.Blocks() as app:
+        gr.Markdown("# 🇲🇦 Terjman-v2")
+        gr.Markdown("Choose a model and enter the English text you want to translate to Moroccan Darija.")
+
+        model_choice = gr.Dropdown(
+            label="Select Model",
+            choices=["Terjman-Nano-v2", "Terjman-Large-v2", "Terjman-Ultra-v2", "Terjman-Supreme-v2"],
+            value="Terjman-Ultra-v2"
+        )
+        input_text = gr.Textbox(label="Input Text", placeholder="Enter text to translate...", lines=3)
+        output_text = gr.Textbox(label="Translated Text", interactive=False, lines=3)
+        translate_button = gr.Button("Translate")
+
+        # Link input and output
+        translate_button.click(
+            fn=translate_text,
+            inputs=[input_text, model_choice],
+            outputs=output_text
+        )
+
+    return app
+
+# Run the app
+if __name__ == "__main__":
+    app = gradio_app()
+    app.launch()