Create app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+# Load your model and tokenizer
+model_name = "akhmat-s/t5-base-grammar-corrector"  # or "akhmat-s/t5-large-quant-grammar-corrector"
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+def correct_grammar(text):
+    inputs = tokenizer.encode("fix: " + text, return_tensors="pt", max_length=512, truncation=True)
+    outputs = model.generate(inputs, max_length=512, num_beams=4, early_stopping=True)
+    corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return corrected_text
+
+iface = gr.Interface(
+    fn=correct_grammar,
+    inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
+    outputs=gr.outputs.Textbox(label="Corrected Text"),
+    title="Grammar Correction Chat",
+    description="Enter text with grammatical errors, and the model will provide corrections."
+)
+
+if __name__ == "__main__":
+    iface.launch()