mBERT Intent Classification Model (v3)
This model is a fine-tuned version of Multilingual BERT (mBERT) for intent classification tasks.
It predicts the intent of a given user input sentence, making it suitable for chatbot, virtual assistant, and NLP applications.
🚀 Model Details
- Model Type: Text Classification
- Base Model: bert-base-multilingual-cased
- Framework: Hugging Face Transformers
- Task: Intent Classification
- Version: v3
🎯 Use Cases
- Chatbots / Virtual Assistants
- Customer support automation
- Banking / fintech intent detection
- Query classification systems
🧠 Labels
⚠️ Update this section based on your actual labels
Example:
| ID | Label |
|---|---|
| 0 | greeting |
| 1 | check_balance |
| 2 | transfer_money |
| 3 | goodbye |
🛠️ How to Use
Load Model & Tokenizer
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
model_id = "tyaisndu/mbert_intent_model_v3"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSequenceClassification.from_pretrained(model_id)
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