README.md

metadata

title: Zero-Shot Text Classifier
emoji: 🏷️
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 5.33.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: Classify text into any custom categories with Qwen3-0.6B

Zero-Shot Text Classifier

Classify any text into your own custom categories using Qwen3-0.6B with zero-shot instruction prompting.

Features

• Custom labels: Define any categories you want
• Multi-label mode: Allow multiple labels to apply simultaneously
• Preset label sets: Quick-start with Sentiment, Topic, Intent, or Tone presets
• Fast inference: ~200ms on GPU via ZeroGPU

Why Qwen3 over BART-MNLI?

• Qwen3-0.6B is smaller (0.6B vs 0.4B) but more capable due to modern architecture
• Handles multi-label classification natively via instruction prompting
• Supports structured JSON output for downstream integration
• Better accuracy on diverse classification tasks (not limited to NLI-style inference)

API Usage

from gradio_client import Client

client = Client("xavier-fuentes/text-classifier")
result = client.predict(
    text="The product quality is amazing but shipping was slow",
    candidate_labels="positive, negative, mixed",
    multi_label=False,
    api_name="/run_classification"
)

Built by Xavier Fuentes @ AI Enablement Academy