initial commit

README.md

@@ -1,8 +1,8 @@
 ---
-title: Roberta Indonesian
-emoji: 🐨
-colorFrom: yellow
-colorTo: indigo
+title: RoBERTa Indonesian
+emoji: 🇮🇩
+colorFrom: red
+colorTo: white
 sdk: streamlit
 app_file: app.py
 pinned: false

app.py

@@ -0,0 +1,63 @@
+import streamlit as st
+from huggingface_hub import InferenceApi
+import pandas as pd
+from transformers import pipeline
+
+STYLE = """
+<style>
+img {
+    max-width: 100%;
+}
+
+th {
+    text-align: left!important
+}
+</style>
+"""
+MASK_TOKEN = "<mask>"
+
+
+def display_table(df):
+    st.subheader("Top 5 Prediction.")
+    df.drop(columns=["token", "token_str"], inplace=True)
+    df = df.style.set_properties(subset=["sequence", "score"], **{"text-align": "left"})
+    st.table(df)
+
+
+def main():
+    st.markdown(STYLE, unsafe_allow_html=True)
+    st.title("Indonesian RoBERTa Base")
+    user_input = st.text_input("Insert a sentence to predict with a mask token: <mask>")
+    mask_api = InferenceApi("flax-community/indonesian-roberta-base")
+
+    emot_name = "StevenLimcorn/indonesian-roberta-base-emotion-classifier"
+    emot_pipeline = pipeline("sentiment-analysis", model=emot_name, tokenizer=emot_name)
+
+    if len(user_input) > 0:
+        try:
+            user_input.index(MASK_TOKEN)
+        except ValueError:
+            st.error("Please enter a sentence with the correct mask token: <mask>")
+        else:
+            # A List of dict with keys: sequence, score, token, token_str
+            result = mask_api(inputs=user_input)
+            df = pd.DataFrame(result)
+            display_table(df)
+
+            # emot
+            st.subheader("Emotion Analysis of the Top 5 Prediction")
+            emot_df = pd.DataFrame(columns=["sequence", "label", "score"])
+            for sequence in df["sequence"].values:
+                emot_output = emot_pipeline(sequence)
+
+                result_dict = {"sequence": sequence}
+                result_dict.update(emot_output[0])
+                emot_df = emot_df.append(result_dict, ignore_index=True)
+
+            emot_df = emot_df.style.set_properties(
+                subset=["sequence", "label", "score"], **{"text-align": "left"}
+            )
+            st.table(emot_df)
+
+
+main()

requirements.txt

@@ -0,0 +1,7 @@
+streamlit
+huggingface_hub
+torch
+jax
+flax
+transformers
+pandas