Upload folder using huggingface_hub

app.py

@@ -1,8 +1,14 @@
 import gradio as gr
 from transformers import pipeline
 from utils import *
+from datasets import load_dataset
 
 pipe = pipeline(model="raminass/scotus-v10", top_k=13, padding=True, truncation=True)
+all = load_dataset("raminass/full_opinions_1994_2020")
+df = pd.DataFrame(all["train"])
+choices = []
+for index, row in df[df.category == "per_curiam"].iterrows():
+    choices.append((f"""{row["case_name"]}""", row["text"]))
 
 max_textboxes = 100
 
@@ -23,9 +29,16 @@ def greet(opinion):
     )
 
 
+def set_input(drop):
+    return drop
+
+
 with gr.Blocks() as demo:
     opinion = gr.Textbox(label="Opinion")
     op_level = gr.outputs.Label(num_top_classes=13, label="Overall")
+
+    drop = gr.Dropdown(choices=sorted(choices))
+
     greet_btn = gr.Button("Predict")
     textboxes = []
     for i in range(max_textboxes):
@@ -36,6 +49,8 @@ with gr.Blocks() as demo:
         textboxes.append(t)
         textboxes.append(par_level)
 
+    drop.select(set_input, inputs=drop, outputs=[opinion])
+
     greet_btn.click(
         fn=greet,
         inputs=opinion,