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import gradio as gr
from transformers import pipeline
# Initialize the classifiers
zero_shot_classifier = pipeline("zero-shot-classification", model="tasksource/ModernBERT-base-nli")
nli_classifier = pipeline("text-classification", model="tasksource/ModernBERT-base-nli")
def process_input(text_input, labels_or_premise, mode):
if mode == "Zero-Shot Classification":
# Clean and process the labels
labels = [label.strip() for label in labels_or_premise.split(',')]
# Get predictions
prediction = zero_shot_classifier(text_input, labels)
results = {label: score for label, score in zip(prediction['labels'], prediction['scores'])}
return results, ''
else: # NLI mode
# Process as premise-hypothesis pair
prediction = nli_classifier([{"text": text_input, "text_pair": labels_or_premise}])
results = {pred['label']: pred['score'] for pred in prediction}
return results, ''
# Create the interface
with gr.Blocks() as demo:
gr.Markdown("# 🤖 ModernBERT Text Analysis")
mode = gr.Radio(
["Zero-Shot Classification", "Natural Language Inference"],
label="Select Mode",
value="Zero-Shot Classification"
)
with gr.Column():
text_input = gr.Textbox(
label="✍️ Input Text",
placeholder="Enter your text...",
lines=3
)
labels_or_premise = gr.Textbox(
label="🏷️ Categories / Premise",
placeholder="Enter comma-separated categories or premise text...",
lines=2
)
submit_btn = gr.Button("Submit")
outputs = [
gr.Label(label="📊 Results"),
gr.Markdown(label="📈 Analysis", visible=False)
]
# Different examples for each mode
zero_shot_examples = [
["I need to buy groceries", "shopping, urgent tasks, leisure, philosophy"],
["The sun is very bright today", "weather, astronomy, complaints, poetry"],
["I love playing video games", "entertainment, sports, education, business"],
["The car won't start", "transportation, art, cooking, literature"],
["She wrote a beautiful poem", "creativity, finance, exercise, technology"]
]
nli_examples = [
["A man is sleeping on a couch", "The man is awake"],
["The restaurant is full of people", "The place is empty"],
["The child is playing with toys", "The kid is having fun"],
["It's raining outside", "The weather is wet"],
["The dog is barking at the mailman", "There is a cat"]
]
def update_examples(mode_value):
return gr.Examples(
zero_shot_examples if mode_value == "Zero-Shot Classification" else nli_examples,
inputs=[text_input, labels_or_premise]
)
mode.change(fn=update_examples, inputs=[mode], outputs=gr.Examples())
submit_btn.click(
fn=process_input,
inputs=[text_input, labels_or_premise, mode],
outputs=outputs
)
# Launch the app
if __name__ == "__main__":
demo.launch() |