Update README for new repo name harpertokenConvAI and remove emojis and noise

README.md

@@ -13,7 +13,7 @@ metrics:
 - exact_match
 - f1_score
 model-index:
-- name: Conversational AI Base Model
+- name: Harpertoken ConvAI
   results:
   - task: 
       type: question-answering
@@ -27,19 +27,13 @@ model-index:
         value: 0.85
 ---
 
-# Conversational AI Base Model
+# Harpertoken ConvAI
 
-<p align="center">
-  <a href="https://huggingface.co/bniladridas/conversational-ai-base-model">
-    <img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" width="200" alt="Hugging Face">
-  </a>
-</p>
+## Model Overview
 
-## 🤖 Model Overview
+A context-aware conversational AI model based on DistilBERT for natural language understanding and generation.
 
-A sophisticated, context-aware conversational AI model built on the DistilBERT architecture, designed for advanced natural language understanding and generation.
-
-### 🌟 Key Features
+### Key Features
 - **Advanced Response Generation**
   - Multi-strategy response mechanisms
   - Context-aware conversation tracking
@@ -55,7 +49,7 @@ A sophisticated, context-aware conversational AI model built on the DistilBERT a
   - Dynamic model loading
   - Error handling and recovery
 
-## 🚀 Quick Start
+## Quick Start
 
 ### Installation
 ```bash
@@ -67,51 +61,37 @@ pip install transformers torch
 from transformers import AutoModelForQuestionAnswering, AutoTokenizer
 
 # Load model and tokenizer
-model = AutoModelForQuestionAnswering.from_pretrained('bniladridas/conversational-ai-base-model')
-tokenizer = AutoTokenizer.from_pretrained('bniladridas/conversational-ai-base-model')
+model = AutoModelForQuestionAnswering.from_pretrained('harpertoken/harpertokenConvAI')
+tokenizer = AutoTokenizer.from_pretrained('harpertoken/harpertokenConvAI')
 ```
 
-## 🧠 Model Capabilities
+## Model Capabilities
 - Semantic understanding of context and questions
 - Ability to extract precise answers
 - Multiple response generation strategies
 - Fallback mechanisms for complex queries
 
-## 📊 Performance
+## Performance
 - Trained on Stanford Question Answering Dataset (SQuAD)
 - Exact Match: 75%
 - F1 Score: 85%
 
-## ⚠️ Limitations
+## Limitations
 - Primarily trained on English text
 - Requires domain-specific fine-tuning
 - Performance varies by use case
 
-## 🔍 Technical Details
+## Technical Details
 - **Base Model:** DistilBERT
 - **Variant:** Distilled for question-answering
 - **Maximum Sequence Length:** 512 tokens
 - **Supported Backends:** TensorFlow, PyTorch
 
-## 🤝 Ethical Considerations
-- Designed with fairness in mind
-- Transparent about model capabilities
-- Ongoing work to reduce potential biases
-
-## 📚 Citation
+## Citation
 ```bibtex
-@misc{conversational-ai-model,
-  title={Conversational AI Base Model},
+@misc{harpertoken-convai,
+  title={Harpertoken ConvAI},
   author={Niladri Das},
   year={2025},
-  url={https://huggingface.co/bniladridas/conversational-ai-base-model}
-}
-```
-
-## 📞 Contact
-- GitHub: [bniladridas](https://github.com/bniladridas)
-- Hugging Face: [@bniladridas](https://huggingface.co/bniladridas)
-
----
-
-*Last Updated: February 2025*
+  url={https://huggingface.co/harpertoken/harpertokenConvAI}
+}