L-MChat
Collection
2 items
•
Updated
L-MChat-Small
This was a test of mine how small merges perform, because there are a lot of 7b merges and higher but not a lot of 2b merges.
Merge Method
This model was merged using the SLERP 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: Weyaxi/Einstein-v4-phi2
layer_range:
- 0
- 32
- model: rhysjones/phi-2-orange-v2
layer_range:
- 0
- 32
merge_method: slerp
base_model: rhysjones/phi-2-orange-v2
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
Usage
Use it with the ChatML format, you can also use the Inference-API for this Model.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 63.14 |
| AI2 Reasoning Challenge (25-Shot) | 61.60 |
| HellaSwag (10-Shot) | 75.90 |
| MMLU (5-Shot) | 57.41 |
| TruthfulQA (0-shot) | 49.94 |
| Winogrande (5-shot) | 74.98 |
| GSM8k (5-shot) | 58.98 |
- Downloads last month
- 2,948
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 Artples/L-MChat-Small
Spaces using Artples/L-MChat-Small 2
Collection including Artples/L-MChat-Small
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard61.600
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard75.900
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard57.410
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard49.940
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard74.980
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard58.980