Spaces:
Sleeping
Sleeping
Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,36 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import streamlit as st
|
2 |
+
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
|
3 |
+
import torch
|
4 |
+
|
5 |
+
# Load pre-trained model and tokenizer (Grammar correction model)
|
6 |
+
@st.cache_resource
|
7 |
+
def load_model():
|
8 |
+
model_name = "prithivida/grammar_error_correcter_v1"
|
9 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
10 |
+
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
|
11 |
+
return tokenizer, model
|
12 |
+
|
13 |
+
tokenizer, model = load_model()
|
14 |
+
|
15 |
+
# Function to correct grammar
|
16 |
+
def correct_grammar(text):
|
17 |
+
input_text = "gec: " + text
|
18 |
+
inputs = tokenizer.encode(input_text, return_tensors="pt", truncation=True)
|
19 |
+
outputs = model.generate(inputs, max_length=512, num_beams=4, early_stopping=True)
|
20 |
+
corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
|
21 |
+
return corrected_text
|
22 |
+
|
23 |
+
# Streamlit UI
|
24 |
+
st.title("📝 Grammar Correction App")
|
25 |
+
st.write("Enter a sentence or paragraph below, and the AI will correct any grammatical errors.")
|
26 |
+
|
27 |
+
user_input = st.text_area("Your Text", height=200, placeholder="Type or paste your text here...")
|
28 |
+
|
29 |
+
if st.button("Correct Grammar"):
|
30 |
+
if user_input.strip():
|
31 |
+
with st.spinner("Correcting grammar..."):
|
32 |
+
corrected = correct_grammar(user_input)
|
33 |
+
st.subheader("✅ Corrected Text")
|
34 |
+
st.success(corrected)
|
35 |
+
else:
|
36 |
+
st.warning("Please enter some text to correct.")
|