A newer version of this model is available:
T145/ZEUS-8B-V2
ZEUS
Taking inspiration from Dampfinchen/Llama-3.1-8B-Ultra-Instruct and brucethemoose, the goal of this merge is to create an abliterated, conversational AI within 8B parameters that's coherent over long conversations. Using "Ultra-Instruct" as a baseline (which has problems with grammar and coherent conversations), preliminary results seem to show these goals are met. Expect responses in the Markdown format by default.
Merge Details
Merge Method
This model was merged using the DARE TIES merge method using meta-llama/Llama-3.1-8B-Instruct as a base.
Models Merged
The following models were included in the merge:
- akjindal53244/Llama-3.1-Storm-8B
- arcee-ai/Llama-3.1-SuperNova-Lite
- Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
Configuration
The following YAML configuration was used to produce this model:
base_model: meta-llama/Llama-3.1-8B-Instruct
dtype: bfloat16
merge_method: dare_ties
parameters:
int8_mask: 1.0
slices:
- sources:
- layer_range: [0, 32]
model: akjindal53244/Llama-3.1-Storm-8B
parameters:
density: 0.7
weight: 0.2
- layer_range: [0, 32]
model: arcee-ai/Llama-3.1-SuperNova-Lite
parameters:
density: 0.7
weight: 0.3
- layer_range: [0, 32]
model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
parameters:
density: 0.7
weight: 0.5
- layer_range: [0, 32]
model: meta-llama/Llama-3.1-8B-Instruct
tokenizer_source: meta-llama/Llama-3.1-8B-Instruct
Open LLM Leaderboard Evaluation Results
Detailed results can be found here!
Metric | Value |
---|---|
Avg. | 29.59 |
IFEval (0-Shot) | 79.41 |
BBH (3-Shot) | 31.39 |
MATH Lvl 5 (4-Shot) | 19.18 |
GPQA (0-shot) | 6.82 |
MuSR (0-shot) | 8.57 |
MMLU-PRO (5-shot) | 32.14 |
- Falls about 1 point behind "Ultra-Instruct" on IFEval and BBH, but everything else is a significant improvement.
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard79.410
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard31.390
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard19.180
- acc_norm on GPQA (0-shot)Open LLM Leaderboard6.820
- acc_norm on MuSR (0-shot)Open LLM Leaderboard8.570
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard32.140