Create app.py

app.py

@@ -0,0 +1,35 @@
+import ctranslate2
+import gradio as gr
+from huggingface_hub import snapshot_download
+from sentencepiece import SentencePieceProcessor
+
+model_name="santhosh/madlad400-3b-ct2"
+
+tokenizer = SentencePieceProcessor()
+model_path = snapshot_download(model_name)
+print(model_path)
+tokenizer.load(f"{model_path}/sentencepiece.model")
+translator = ctranslate2.Translator(model_path)
+
+def translate(input_text, target_language):
+    input_tokens = tokenizer.encode(f"<2{target_language}> {input_text}", out_type=str)
+    results = translator.translate_batch(
+        [input_tokens],
+        batch_type="tokens",
+        # max_batch_size=1024,
+        beam_size=1,
+        no_repeat_ngram_size=1,
+        # repetition_penalty=2,
+    )
+    translated_sentence = tokenizer.decode(results[0].hypotheses[0])
+    return translated_sentence
+
+def translate_interface(input_text, target_language):
+    translated_text = translate(input_text, target_language)
+    return translated_text
+
+input_text = gr.Textbox(label="Input Text", value="Imagine a world in which every single person on the planet is given free access to the sum of all human knowledge. ")
+target_language = gr.Textbox(value="ml", label="Target Language")
+output_text = gr.Textbox(label="Translated Text")
+
+gr.Interface(fn=translate_interface, inputs=[input_text, target_language], outputs=output_text).launch()