Create app.py

app.py

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+import streamlit as st
+import transformers
+import tensorflow
+import PIL
+from PIL import Image
+import time
+from transformers import pipeline
+
+model_checkpoint = "Modfiededition/t5-base-fine-tuned-on-jfleg"
+
+
+@st.cache(allow_output_mutation=True, suppress_st_warning=True)
+def load_model():
+    return pipeline("text2text-generation", model=model_checkpoint)
+model = load_model()
+
+    
+#prompts
+st.title("Writing Assistant for you 🤖")
+st.markdown("This writing assistant detects and corrects grammatical mistakes for you! This assitant uses **T5-base model ✍️** fine-tuned on jfleg dataset.")
+#image = Image.open('new_grammar.jpg')
+#st.image(image, caption='Image Credit: https://abrc.org.au/wp-content/uploads/2020/12/Grammar-checker.jpg')
+st.subheader("Some examples: ")
+example_1 = st.button("I am write on AI")
+example_2 = st.button("This sentence has, bads grammar mistake!")
+
+textbox = st.text_area('Write your text in this box:', '',height=100,  max_chars=500 )
+
+button = st.button('Detect grammar mistakes:')
+
+# output
+st.subheader("Correct sentence: ")
+if example_1:
+    with st.spinner('In progress.......'):
+        output_text = model("I am write on AI")[0]["generated_text"]
+    st.markdown("## "+output_text)
+
+if example_2:
+    with st.spinner('In progress.......'):
+        output_text = model("This sentence has, bads grammar mistake!")[0]["generated_text"]
+    st.markdown("## "+output_text)
+if button:
+    with st.spinner('In progress.......'):
+        if textbox:
+            output_text = model(textbox)[0]["generated_text"]
+        else:
+            output_text = " "
+    st.markdown("## "+output_text)