Model mera-mix-4x7B
This is a mixture of experts (MoE) model that is half as large (4 experts instead of 8) as the Mixtral-8x7B while been comparable to it across different benchmarks. You can use it as a drop in replacement for your Mixtral-8x7B and get much faster inference.
mera-mix-4x7B achieves the score of 75.91 on the OpenLLM Eval and compares well with 72.7 by Mixtral-8x7B and 74.46 by Mixtral-8x22B.
You can try the model with the Mera Mixture Chat.
In addition, to the official Open LLM Leaderboard, the results on OpenLLM Eval have been validated by others as well (76.59).
Our own initial eval is available here (76.37).
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 75.91 |
AI2 Reasoning Challenge (25-Shot) | 72.95 |
HellaSwag (10-Shot) | 89.17 |
MMLU (5-Shot) | 64.44 |
TruthfulQA (0-shot) | 77.17 |
Winogrande (5-shot) | 85.64 |
GSM8k (5-shot) | 66.11 |
- Downloads last month
- 5,707
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 meraGPT/mera-mix-4x7B
Spaces using meraGPT/mera-mix-4x7B 2
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard72.950
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard89.170
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.440
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard77.170
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard85.640
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard66.110