Finch 7B Merge
A SLERP merge of two powerful 7B language models
Description
Finch is a 7B language model created by merging macadeliccc/WestLake-7B-v2-laser-truthy-dpo and SanjiWatsuki/Kunoichi-DPO-v2-7B using the SLERP method.
Quantized Models
Quantized versions of Finch are available:
Recommended Settings
For best results, use the ChatML format with the following sampler settings:
Temperature: 1.2 Min P: 0.2 Smoothing Factor: 0.2
Mergekit Configuration
base_model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo dtype: float16 merge_method: slerp parameters: t: - filter: self_attn value: [0.0, 0.5, 0.3, 0.7, 1.0] - filter: mlp value: [1.0, 0.5, 0.7, 0.3, 0.0] - value: 0.5 slices: - sources: - layer_range: [0, 32] model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo - layer_range: [0, 32] model: SanjiWatsuki/Kunoichi-DPO-v2-7B
Evaluation Results
Finch's performance on the Open LLM Leaderboard:
| Metric | Value |
|---|---|
| Avg. | 73.78 |
| AI2 Reasoning Challenge (25-Shot) | 71.59 |
| HellaSwag (10-Shot) | 87.87 |
| MMLU (5-Shot) | 64.81 |
| TruthfulQA (0-shot) | 67.96 |
| Winogrande (5-shot) | 84.14 |
| GSM8k (5-shot) | 66.34 |
Detailed results: https://huggingface.co/datasets/open-llm-leaderboard/details_antiven0m__finch
- Downloads last month
- 15
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
Ask for provider support
Model tree for antiven0m/finch
Merge model
this model
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard71.590
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard87.870
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.810
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard67.960
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard84.140
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard66.340