new apps

app.py

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+import gradio as gr
+from transformers import MBart50TokenizerFast, MBartForConditionalGeneration
+
+# Load the model and tokenizer from Hugging Face Hub
+model_name = "Aesopskenya/GikuyuToEnglishTranslator"
+tokenizer = MBart50TokenizerFast.from_pretrained(model_name)
+model = MBartForConditionalGeneration.from_pretrained(model_name)
+
+def translate_gikuyu(sentence):
+    # Tokenize input
+    inputs = tokenizer(sentence, return_tensors="pt", truncation=True, padding=True, max_length=128)
+    
+    # Generate translation
+    outputs = model.generate(inputs.input_ids, max_length=128)
+    
+    # Decode output
+    translation = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return translation
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=translate_gikuyu,
+    inputs="text",
+    outputs="text",
+    title="Gikuyu-English Translator",
+    description="Enter a Gikuyu sentence, and the model will translate it into English."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

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+transformers
+gradio
+torch
+python-dotenv