Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: Test157t/Prima-Pastacles-7b
layer_range: [0, 32]
- model: Test157t/Pasta-Sea-7b-128k
layer_range: [0, 32]
merge_method: slerp
base_model: Test157t/Prima-Pastacles-7b
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 70.36 |
AI2 Reasoning Challenge (25-Shot) | 68.09 |
HellaSwag (10-Shot) | 86.57 |
MMLU (5-Shot) | 64.58 |
TruthfulQA (0-shot) | 62.51 |
Winogrande (5-shot) | 81.06 |
GSM8k (5-shot) | 59.36 |
- Downloads last month
- 26
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for Nitral-Archive/Prima-Pastacles-7b-128k
Base model
Nitral-Archive/Prima-Pastacles-7bEvaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard68.090
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard86.570
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.580
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard62.510
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard81.060
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard59.360