nbeerbower/Llama3.1-Gutenberg-Doppel-70B
The nbeerbower/Llama3.1-Gutenberg-Doppel-70B is a 70 billion parameter language model, fine-tuned from mlabonne/Hermes-3-Llama-3.1-70B-lorablated. This model was ORPO-tuned using the jondurbin/gutenberg-dpo-v0.1 and nbeerbower/gutenberg2-dpo datasets, specializing in text generation and understanding with a focus on literary style. It is designed for tasks requiring nuanced language and creative text output, leveraging its extensive training on diverse literary sources.
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Llama3.1-Gutenberg-Doppel-70B Overview
This model, developed by nbeerbower, is a 70 billion parameter language model built upon the Llama 3.1 architecture. It is a fine-tuned version of mlabonne/Hermes-3-Llama-3.1-70B-lorablated.
Key Capabilities
- ORPO Tuning: The model was fine-tuned using the ORPO (Odds Ratio Preference Optimization) method over 3 epochs, leveraging two H100 GPUs. This method is known for effectively aligning models with human preferences.
- Literary Data Training: It was specifically trained on the jondurbin/gutenberg-dpo-v0.1 and nbeerbower/gutenberg2-dpo datasets, suggesting a specialization in generating text with a literary or classic style.
Performance Metrics
Evaluations on the Open LLM Leaderboard show the following average scores:
- Avg.: 35.68
- IFEval (0-Shot): 70.92
- BBH (3-Shot): 52.56
- MMLU-PRO (5-shot): 41.52
Good For
- Generating text in a literary or classic style.
- Tasks requiring nuanced language understanding and generation.
- Applications benefiting from a model trained on extensive literary datasets.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.