Upload interface_MT_fo_en.py

interface_MT_fo_en.py

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+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+# Path to your model's checkpoints
+model_checkpoint_path = "barbaroo/nllb_200_600M_fo_en"
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(model_checkpoint_path)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint_path)
+
+# Function to perform translation
+def translate(text, model, tokenizer):
+    # Encode the text
+    inputs = tokenizer.encode(text, return_tensors="pt")
+
+    # Generate translation outputs
+    outputs = model.generate(inputs, max_length=80, num_beams=4, early_stopping=True)
+
+    # Decode and return the translated text
+    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return translated_text
+
+# Sample translation (You can comment this out when deploying to Gradio)
+faroese_text = "Granskingarvirksemi fevnir bæði um føroyskar og altjóða granskingarverkætlanir."
+translated_text = translate(faroese_text, model, tokenizer)
+print(translated_text)
+
+# Gradio Interface setup
+# Ensure Gradio is installed
+!pip install gradio
+
+# Importing Gradio
+import gradio as gr
+
+# Define the Gradio interface
+def gradio_translate(text):
+    return translate(text, model, tokenizer)
+
+iface = gr.Interface(fn=gradio_translate, 
+                     inputs="text", 
+                     outputs="text", 
+                     title="Faroese to English Translator",
+                     description="Translate Faroese text to English using a state-of-the-art model.")
+
+# Launch the interface
+iface.launch()