---
base_model: unsloth/llama-2-7b-chat-bnb-4bit
datasets:
  - piotr25691/ultrachat-200k-alpaca
language:
  - en
library_name: peft
license: apache-2.0
pipeline_tag: text-generation
---

# Xander
Welcome to the Xander Conversational Model repository! This model has been fine-tuned from the unsloth/llama-2-7b-chat-bnb-4bit base on the piotr25691/ultrachat-200k-alpaca dataset to enhance its conversational abilities. It is designed to provide more natural, engaging, and contextually aware responses.

# Introduction
The Xander Conversational Model is an advanced NLP model aimed at improving interactive text generation. By leveraging the strengths of unsloth/llama-2-7b-chat-bnb-4bit and fine-tuning it with the extensive piotr25691/ultrachat-200k-alpaca dataset, the model is adept at generating coherent and contextually relevant conversations.

# Features
- Improved Conversational Flow: Generates more natural and engaging responses.
- Context Awareness: Maintains context over multiple interactions.
- Customizable: Can be further fine-tuned for specific applications or industries.

# Dataset
The model was fine-tuned on the piotr25691/ultrachat-200k-alpaca dataset, which consists of 200,000 high-quality conversational pairs. This dataset helps the model to understand and generate more nuanced and contextually appropriate responses.

# Performance
The model has shown significant improvements in generating more human-like responses compared to its base. Here are some key metrics:

- Perplexity: Lower perplexity indicating better language modeling performance.
- Response Coherence: Improved coherence in multi-turn conversations.
- Engagement: Higher user satisfaction in interactive scenarios.