PetroGPT/WestSeverus-7B-DPO-v2
PetroGPT/WestSeverus-7B-DPO-v2 is a 7 billion parameter language model from the WestLake Family, fine-tuned using DPO over WestSeverus-7B. It demonstrates strong performance in basic math problems and excels on the TruthfulQA and BigBench benchmarks. This model is designed for research and reference in mathematics, chemistry, physics, and coding, offering an 8192 token context length.
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WestSeverus-7B-DPO-v2 Overview
WestSeverus-7B-DPO-v2 is a 7 billion parameter model, part of the WestLake Family, developed by PetroGPT. It is an instruction-tuned model, specifically trained using Direct Preference Optimization (DPO) on various datasets, building upon the base model WestSeverus-7B. The model is noted for its 8192 token context length.
Key Capabilities & Performance
- Mathematical Proficiency: Demonstrates good performance on basic math problems.
- Benchmark Excellence: Achieves top scores on the YALL - Yet Another LLM Leaderboard, particularly outperforming on TruthfulQA (72.72) and BigBench (48.71) among comparable 7B models.
- Open LLM Leaderboard: Ranks highly among 7B models, with strong results in TruthfulQA (72.37) and GSM8K (71.65).
- Coding Potential: While HumanEval scores are 43.3, it is suggested for further research and reference in coding.
Use Cases
This model is suitable for applications requiring:
- Mathematical Problem Solving: Especially basic arithmetic and logical reasoning.
- Scientific Research: Applicable in chemistry, physics, and related fields for reference and analysis.
- Coding Assistance: Can be utilized for research and reference in programming tasks.
WestSeverus-7B-DPO-v2 uses the ChatML prompt format with system prompts, facilitating structured interactions.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.