llama2-7b-function-calling-slerp
llama2-7b-function-calling-slerp is a merge of the following models using mergekit:
🧩 Configuration
slices:
- sources:
- model: meta-llama/Llama-2-7b-hf
layer_range: [0, 32]
- model: Trelis/Llama-2-7b-chat-hf-function-calling-v3
layer_range: [0, 32]
merge_method: slerp
base_model: meta-llama/Llama-2-7b-hf
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. | 53.53 |
| AI2 Reasoning Challenge (25-Shot) | 55.46 |
| HellaSwag (10-Shot) | 79.50 |
| MMLU (5-Shot) | 50.32 |
| TruthfulQA (0-shot) | 40.32 |
| Winogrande (5-shot) | 75.22 |
| GSM8k (5-shot) | 20.39 |
- Downloads last month
- 77
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.
Space using Aabbhishekk/llama2-7b-function-calling-slerp 1
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard55.460
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard79.500
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard50.320
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard40.320
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard75.220
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard20.390