Upload 3 files

app.py

@@ -0,0 +1,48 @@
+from simpletransformers.classification import ClassificationModel, ClassificationArgs
+import os
+import torch
+import pandas as pd
+import streamlit as st
+
+model_types = {
+    "bert": "cahya/bert-base-indonesian-522M", 
+    "roberta":"cahya/roberta-base-indonesian-522M"}
+model_name = "bert"
+
+class_names = ['none', 'E', 'S', 'G']
+
+# Create a new instance of the model with the same architecture
+model_args = ClassificationArgs()
+model_args.use_cuda = False  # Use CPU
+
+loaded_model = ClassificationModel(
+    model_name, model_types[model_name], num_labels=len(class_names), args=model_args,use_cuda=False
+)
+
+# Load the state dictionary into the model
+loaded_model.model.load_state_dict(torch.load('model_state_dict.pt', map_location=torch.device('cpu')))
+
+def run():
+    # create form 
+    with st.form("form"):
+        text_input = st.text_input("Enter some text")
+        if text_input:
+            st.write(f"Text input: {text_input}")
+        st.markdown("---")
+
+        submitted = st.form_submit_button("predict")
+
+    data_inf = {
+        "text" : text_input
+    }
+
+    data_inf = pd.DataFrame([data_inf])
+    st.dataframe(data_inf)
+
+
+    if submitted:
+        predictions, raw_outputs = loaded_model.predict([data_inf["text"][0]])
+        st.write("# ESG Category: ", class_names[int(predictions[0])])
+
+if __name__=="__main__":
+    run()

model_state_dict.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:baa445d294b8e64c7066819ed04e5574df66f2e7f1e5d57b1e0b1e51b26a0abb
+size 442562325

requirements.txt

@@ -0,0 +1,4 @@
+pandas==1.5.3
+simpletransformers==0.70.1
+torch==2.2.1
+streamlit