Create README.md

README.md

@@ -0,0 +1,88 @@
+---
+license: other
+task_categories:
+- text-generation
+language:
+- hi
+- en
+tags:
+- persona
+- emotional
+- chatbot
+- humanlike
+- roleplay
+---
+
+## 💬 Dataset Summary
+
+| Field         | Description                        |
+| ------------- | ---------------------------------- |
+| **Name**      | `Abhaykoul/priya-v1`               |
+| **Creator**   | Abhay Koul (HelpingAI)             |
+| **Language**  | English                            |
+| **Use Case**  | Persona-based Chatbot Training     |
+| **Instances** | ~7,640                             |
+| **Splits**    | Train Only                         |
+| **Schema**    | instruction, input, output, system |
+
+---
+
+## 🧩 Dataset Structure
+
+Each data entry includes structured conversational information to simulate persona-based dialogue:
+
+```json
+{
+  "system": "You are Priya Razdan, a 17-year-old Kashmiri Pandit girl...",
+  "instruction": "What do you think about long-distance relationships?",
+  "input": "",
+  "output": "Honestly, it depends on the trust. Distance isn't the problem; silence is."
+}
+```
+
+* **instruction** → user query or prompt
+* **input** → optional context (usually empty)
+* **output** → Priya’s emotionally expressive reply
+* **system** → defines the persona and behavioral traits
+
+---
+
+## 🎯 Purpose & Applications
+
+The **Priya-v1** dataset was developed to:
+
+* Build **emotionally intelligent dialogue systems**
+* Train **persona-consistent LLMs / LEMs**
+* Enhance **context retention** and **style coherence**
+* Support **fine-tuning** of character-based conversational agents
+* Explore **empathetic and personality-rich response generation**
+
+---
+
+## ⚙️ Technical Details
+
+* **Format:** JSONL / Parquet
+* **Instances:** ~7.6K high-quality entries
+* **Data Split:** Train (100%)
+* **Source Type:** Synthetic + Curated Human-like Dialogues
+* **Data Origin:** Constructed internally by HelpingAI’s conversational design team
+
+---
+
+## 🧭 Intended Use
+
+| Use Case                    | Example                                                  |
+| --------------------------- | -------------------------------------------------------- |
+| Persona Chatbot Fine-tuning | Enhance emotional realism in chatbot personalities       |
+| Dialogue Research           | Study persona consistency and empathy in model responses |
+| Style Conditioning          | Model character-specific tones and emotional depth       |
+
+---
+
+## ⚠️ Limitations & Biases
+
+* **Single Persona Focus:** Dataset revolves around one persona — limited speaker diversity.
+* **Cultural Context:** Priya’s identity may influence responses stylistically.
+* **Emotional Framing:** Emphasis on personality and emotion may bias factual neutrality.
+
+Use responsibly in adaptive systems, ensuring persona tone does not override factual accuracy or ethical standards.