Understand Intent, Find Nearby Solutions 💡 bert-local is an intelligent AI assistant powered by bert-mini, designed to interpret natural, conversational queries and suggest precise local business categories in real time. Unlike traditional map services that struggle with NLP, bert-local captures personal intent to deliver actionable results—whether it’s finding a 🐾 pet store for a sick dog or a 💼 accounting firm for tax help.
With support for 140+ local business categories and a compact model size of ~20MB, bert-local combines open-source datasets and advanced fine-tuning to overcome the limitations of Google Maps’ NLP. Open source and extensible, it’s perfect for developers and businesses building context-aware local search solutions on edge devices and mobile applications. 🚀
Intent-Driven 🧠: Understands natural language queries like “My dog isn’t eating” to suggest 🐾 pet stores or 🩺 veterinary clinics.
Accurate & Fast ⚡: Achieves 94.26% test accuracy (115/122 correct) for precise category predictions in real time.
Extensible 🛠️: Open source and customizable with your own datasets (e.g., ChatGPT, Grok, or proprietary data).
Comprehensive 🏪: Supports 140+ local business categories, from 💼 accounting firms to 🦒 zoos.
Lightweight 📱: Compact ~20MB model size, optimized for edge devices and mobile applications.
“bert-local transformed our app’s local search—it feels like it gets the user!” — App Developer 💬
Key Features ✨
Advanced NLP 📜: Built on bert-mini, fine-tuned for multi-class text classification.
Real-Time Results ⏱️: Delivers category suggestions instantly, even for complex queries.
Wide Coverage 🗺️: Matches queries to 140+ business categories with high confidence.
Developer-Friendly 🧑💻: Easy integration with Python 🐍, Hugging Face 🤗, and custom APIs.
Open Source 🌐: Freely extend and adapt for your needs.
🔧 How to Use
python
1from transformers import pipeline # 🤗 Import Hugging Face pipeline23# 🚀 Load the fine-tuned intent classification model4classifier = pipeline("text-classification", model="boltuix/bert-local")56# 🧠 Predict the user's intent from a sample input sentence7result = classifier("Where can I see ocean creatures behind glass?")# 🐠 Expecting Aquarium89# 📊 Print the classification result with label and confidence score10print(result)# 🖨️ Example output: [{'label': 'aquarium', 'score': 0.999}]
Supported Categories 🏪
bert-local supports 140 local business categories, each paired with an emoji for clarity:
