Text Classification
Transformers
Safetensors
English
bert
multi-text-classification
classification
intent-classification
intent-detection
nlp
natural-language-processing
edge-ai
iot
smart-home
location-intelligence
voice-assistant
conversational-ai
real-time
bert-local
bert-mini
local-search
business-category-classification
fast-inference
lightweight-model
on-device-nlp
offline-nlp
mobile-ai
multilingual-nlp
intent-routing
category-detection
query-understanding
artificial-intelligence
assistant-ai
smart-cities
customer-support
productivity-tools
contextual-ai
semantic-search
user-intent
microservices
smart-query-routing
industry-application
aiops
domain-specific-nlp
location-aware-ai
intelligent-routing
edge-nlp
smart-query-classifier
zero-shot-classification
smart-search
location-awareness
contextual-intelligence
geolocation
query-classification
multilingual-intent
chatbot-nlp
enterprise-ai
sdk-integration
api-ready
developer-tools
real-world-ai
geo-intelligence
embedded-ai
smart-routing
voice-interface
smart-devices
contextual-routing
fast-nlp
data-driven-ai
inference-optimization
digital-assistants
neural-nlp
ai-automation
lightweight-transformers
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README.md
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from transformers import AutoModelForSequenceClassification
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# 📥 Load the fine-tuned intent classification model
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model = AutoModelForSequenceClassification.from_pretrained("bert-local")
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# 🏷️ Extract the ID-to-label mapping dictionary
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label_mapping = model.config.id2label
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from transformers import AutoModelForSequenceClassification
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# 📥 Load the fine-tuned intent classification model
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model = AutoModelForSequenceClassification.from_pretrained("boltuix/bert-local")
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# 🏷️ Extract the ID-to-label mapping dictionary
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label_mapping = model.config.id2label
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