🚀 Fresh start

app.py

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+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import gradio as gr
+import torch
+
+# Load from Hugging Face model hub
+model_path = "mbalajibalu/grammar-model"
+
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
+
+def correct_grammar(text):
+    if not text.strip():
+        return "Please enter some text to correct."
+    
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_length=512,
+            num_beams=5,
+            early_stopping=True,
+            do_sample=False
+        )
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+iface = gr.Interface(
+    fn=correct_grammar,
+    inputs=gr.Textbox(label="Enter text to correct", placeholder="Type here...", lines=3),
+    outputs=gr.Textbox(label="Corrected text", lines=3),
+    title="Grammar Correction",
+    description="Fixes grammar using a fine-tuned T5 model.",
+    examples=["She go to market.", "He don't like it.", "We was playing."]
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

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+transformers==4.36.2
+torch==2.1.2
+gradio==4.8.0