viethq188/LeoScorpius-7B-Chat-DPO
LeoScorpius-7B-Chat-DPO is a 7 billion parameter language model developed by viethq188, fine-tuned using DPO with the Nectar dataset. This model is optimized for chat applications and demonstrates strong performance, ranking highly on the Hugging Face Open LLM Leaderboard. It is designed for general conversational use cases, leveraging its DPO fine-tuning for improved response quality.
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Overview
viethq188/LeoScorpius-7B-Chat-DPO is a 7 billion parameter language model developed by viethq188. This model has been fine-tuned using Direct Preference Optimization (DPO) with the Nectar dataset, aiming to enhance its conversational capabilities and response quality.
Key Capabilities
- High Performance: Achieved a notable ranking on the Hugging Face Open LLM Leaderboard, placing 3rd overall and 1st among 7B parameter models at the time of its update (December 14th, 2023).
- DPO Fine-tuning: Leverages DPO for improved alignment and preference-based learning, which typically results in more helpful and harmless outputs.
- Chat-Optimized: Specifically designed and fine-tuned for chat and conversational applications.
Usage
This model utilizes an Alpaca-style template for prompts, making it straightforward to integrate into existing workflows that support this format. The recommended template structure is:
{system}
### Instruction:
{prompt}
### Response:Good For
- General-purpose conversational AI.
- Applications requiring a highly-ranked 7B model for chat interactions.
- Developers looking for a DPO-tuned model with strong benchmark performance.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.