9B Role-Playing Merges
Collection
All of my 9B merges go here. Safetensors format.
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7 items
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Updated
Infinite-Laymons-9B
Infinite-Laymons-9B is intended for fictional role-play and storytelling.
The focus is on original responses and elimitation, or reduction of refusals.
Merge Details
This is a merge of pre-trained language models created using mergekit.
Merge Method
This model was merged using the passthrough merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: Nitral-AI/Infinitely-Laydiculous-7B
layer_range: [0, 20]
- sources:
- model: ABX-AI/Infinite-Laymons-7B
layer_range: [12, 32]
merge_method: passthrough
dtype: float16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 67.29 |
| AI2 Reasoning Challenge (25-Shot) | 65.61 |
| HellaSwag (10-Shot) | 84.14 |
| MMLU (5-Shot) | 64.53 |
| TruthfulQA (0-shot) | 54.87 |
| Winogrande (5-shot) | 80.82 |
| GSM8k (5-shot) | 53.75 |
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Model tree for ABX-AI/Infinite-Laymons-9B
Base model
Nitral-AI/Infinitely-Laydiculous-7BCollection including ABX-AI/Infinite-Laymons-9B
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard65.610
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard84.140
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.530
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard54.870
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard80.820
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard53.750