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--- |
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base_model: unsloth/llama-2-7b-chat-bnb-4bit |
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datasets: |
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- piotr25691/ultrachat-200k-alpaca |
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language: |
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- en |
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library_name: peft |
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license: apache-2.0 |
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pipeline_tag: text-generation |
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--- |
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# Xander |
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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. |
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# Introduction |
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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. |
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# Features |
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- Improved Conversational Flow: Generates more natural and engaging responses. |
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- Context Awareness: Maintains context over multiple interactions. |
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- Customizable: Can be further fine-tuned for specific applications or industries. |
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# Dataset |
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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. |
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# Performance |
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The model has shown significant improvements in generating more human-like responses compared to its base. Here are some key metrics: |
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- Perplexity: Lower perplexity indicating better language modeling performance. |
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- Response Coherence: Improved coherence in multi-turn conversations. |
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- Engagement: Higher user satisfaction in interactive scenarios. |
