Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# Load your model and tokenizer from Hugging Face
+model_name = "Addaci/byt5-small-finetuned-yiddish-experiment-10"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+def correct_yiddish_transcription(input_text):
+    inputs = tokenizer(input_text, return_tensors="pt", truncation=True)
+    outputs = model.generate(**inputs)
+    corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return corrected_text
+
+# Create Gradio Interface
+interface = gr.Interface(
+    fn=correct_yiddish_transcription,
+    inputs=gr.Textbox(lines=5, label="Input Yiddish Text"),
+    outputs=gr.Textbox(label="Corrected Text"),
+    title="Yiddish Transcription Correction",
+    description="Corrects raw Yiddish machine transcription using a fine-tuned ByT5 model."
+)
+
+interface.launch()