L3.1-Moe
Collection
https://github.com/moeru-ai/L3.1-Moe
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L3.1-Moe-2x8B-v0.2
This model is a Mixture of Experts (MoE) made with mergekit-moe. It uses the following base models:
Heavily inspired by mlabonne/Beyonder-4x7B-v3.
Quantized models
GGUF by mradermacher
Mergekit config
mergekit_moe_config.yml
base_model: Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base
gate_mode: hidden
dtype: bfloat16
experts:
- source_model: Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base
positive_prompts: &common_prompts
- "chat"
- "assistant"
- "tell me"
- "explain"
- "I want"
- "code"
- "python"
- "javascript"
- "programming"
- "algorithm"
- "reason"
- "math"
- "mathematics"
- "solve"
- "count"
negative_prompts: &rp_prompts
- "storywriting"
- "write"
- "scene"
- "story"
- "character"
- source_model: ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.2
positive_prompts: *rp_prompts
negative_prompts: *common_prompts
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 28.59 |
| IFEval (0-Shot) | 73.48 |
| BBH (3-Shot) | 32.95 |
| MATH Lvl 5 (4-Shot) | 15.26 |
| GPQA (0-shot) | 6.71 |
| MuSR (0-shot) | 11.38 |
| MMLU-PRO (5-shot) | 31.76 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard73.480
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard32.950
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard15.260
- acc_norm on GPQA (0-shot)Open LLM Leaderboard6.710
- acc_norm on MuSR (0-shot)Open LLM Leaderboard11.380
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard31.760