--- language: - en license: apache-2.0 library_name: transformers pipeline_tag: text-classification tags: - modernbert - intent-classification - chatbot - enterprise-chatbot - nlp - text-classification base_model: answerdotai/ModernBERT-base --- # ModernBERT Chatbot Intent Classifier A fine-tuned **ModernBERT** model for enterprise chatbot intent classification. This model classifies user queries into predefined intent categories and is designed to be used as the first stage of a chatbot pipeline before Retrieval-Augmented Generation (RAG) or other downstream workflows. --- # Supported Intents The model predicts one of the following intents: - Business - Greeting - SmallTalk - Complaint - Feedback - Thanks - Goodbye - OutOfDomain --- # Intended Use This model is designed for: - Enterprise AI Chatbots - Customer Support Bots - HR Assistants - Knowledge Base Assistants - Intent Detection - Query Routing - RAG Pipeline Routing Example flow: ``` User Query │ ▼ Intent Classifier │ ├── Business │ └── RAG Pipeline │ ├── Greeting │ └── Greeting Response │ ├── SmallTalk │ └── Small Talk Response │ ├── Complaint │ └── Complaint Workflow │ ├── Feedback │ └── Feedback Workflow │ ├── Thanks │ └── Thank You Response │ ├── Goodbye │ └── Goodbye Response │ └── OutOfDomain └── Reject Politely ``` --- # Base Model - **Model:** answerdotai/ModernBERT-base - **Task:** Sequence Classification - **Framework:** Hugging Face Transformers - **Language:** English --- # Example Usage ```python from transformers import pipeline classifier = pipeline( "text-classification", model="yogeshpandey586/chatbot-intent-classifier" ) print(classifier("Hello")) print(classifier("What services do you provide?")) print(classifier("Tell me a joke")) ``` Example Output ```python [ { "label": "Greeting", "score": 0.998 } ] ``` --- # Training Dataset The model was fine-tuned using a custom intent classification dataset containing manually labeled chatbot queries. Each sample contains: - User Query - Intent Label Example: | Query | Intent | |-------|--------| | Hello | Greeting | | Hi | Greeting | | Good Morning | Greeting | | What services do you provide? | Business | | How can I reset my password? | Business | | Tell me a joke | SmallTalk | | Thanks | Thanks | | Bye | Goodbye | | I have feedback | Feedback | | Your service is bad | Complaint | | Who won yesterday's IPL match? | OutOfDomain | --- # Training Details - Base Model: ModernBERT-base - Fine-tuning Task: Sequence Classification - Framework: Hugging Face Transformers - Optimizer: AdamW - Loss Function: Cross Entropy Loss --- # Evaluation The model was evaluated using a validation dataset. Evaluation Metric: - Accuracy This model is intended for production chatbot routing where low latency and high intent classification accuracy are required. --- # Limitations This model is intended only for intent classification. It is **not** designed for: - Toxicity Detection - Sentiment Analysis - Emotion Detection - Translation - Summarization - Question Answering - Text Generation Performance may decrease on: - Languages other than English - Ambiguous user queries - Multi-intent queries - Queries outside the training domain --- # Production Architecture ``` User Query │ ▼ ModernBERT Intent Classifier │ ▼ Intent Router │ ├── Business → RAG ├── Greeting → Greeting Service ├── SmallTalk → Small Talk Service ├── Complaint → Complaint Service ├── Feedback → Feedback Service ├── Thanks → Thank You Service ├── Goodbye → Goodbye Service └── OutOfDomain → Reject Response ``` --- # Technical Specifications | Property | Value | |----------|-------| | Architecture | ModernBERT | | Base Model | answerdotai/ModernBERT-base | | Framework | Transformers | | Task | Sequence Classification | | Language | English | | Deployment | CPU / GPU | --- # Developer **Yogesh Pandey** AI Developer --- # License Apache-2.0 --- # Citation ```bibtex @misc{yogeshpandey2026intentclassifier, title={ModernBERT Chatbot Intent Classifier}, author={Yogesh Pandey}, year={2026}, publisher={Hugging Face} } ```