nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated

Model Overview

nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated is a 12 billion parameter language model with a 32768 token context length, created by nbeerbower. It was developed using the task arithmetic merge method, combining flammenai/Mahou-1.5-mistral-nemo-12B and nbeerbower/Mistral-Nemo-12B-abliterated-LORA.

Key Characteristics

• Architecture: A merged model based on Mistral and Nemo architectures.
• Merge Method: Utilizes the task arithmetic method for combining pre-trained models.
• Parameter Count: 12 billion parameters.
• Context Length: Supports a context window of 32768 tokens.

Performance Benchmarks

Evaluated on the Open LLM Leaderboard, the model achieved an average score of 26.45. Specific benchmark results include:

• IFEval (0-Shot): 68.25
• BBH (3-Shot): 36.08
• MATH Lvl 5 (4-Shot): 5.29
• GPQA (0-shot): 3.91
• MuSR (0-shot): 16.55
• MMLU-PRO (5-shot): 28.60

Use Cases

This model is suitable for general language generation and understanding tasks, particularly where a blend of capabilities from its constituent models is beneficial. Its performance metrics suggest potential for applications requiring instruction following and basic reasoning, though specialized tasks might require further fine-tuning.