eren23/dpo-binarized-NeuralTrix-7B
The eren23/dpo-binarized-NeuralTrix-7B is a 7 billion parameter language model, fine-tuned using Direct Preference Optimization (DPO) on the argilla/OpenHermes2.5-dpo-binarized-alpha dataset. This model is based on the CultriX/NeuralTrix-7B-dpo architecture and is optimized for general language understanding and generation tasks. It demonstrates competitive performance across various benchmarks, making it suitable for applications requiring robust conversational AI and text completion.
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Overview
eren23/dpo-binarized-NeuralTrix-7B is a 7 billion parameter language model developed by eren23. It leverages the CultriX/NeuralTrix-7B-dpo architecture and has been fine-tuned using Direct Preference Optimization (DPO). The training utilized the argilla/OpenHermes2.5-dpo-binarized-alpha dataset, which is derived from teknium/OpenHermes-2.5 and processed with argilla-io/distilabel.
Key Capabilities & Performance
This model demonstrates strong performance across a range of benchmarks, as evaluated on the Open LLM Leaderboard. Its average score is 76.17, indicating solid general-purpose capabilities. Specific benchmark results include:
- AI2 Reasoning Challenge (25-Shot): 72.35
- HellaSwag (10-Shot): 88.89
- MMLU (5-Shot): 64.09
- TruthfulQA (0-shot): 79.07
- Winogrande (5-shot): 84.61
- GSM8k (5-shot): 68.01
Good For
- General text generation and understanding tasks.
- Applications requiring a model with a balanced performance across reasoning, common sense, and language comprehension.
- Use cases where a 7B parameter model offers a good balance between performance and computational efficiency.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.