MixTAO-7Bx2-MoE
MixTAO-7Bx2-MoE is a Mixture of Experts (MoE). This model is mainly used for large model technology experiments, and increasingly perfect iterations will eventually create high-level large language models.
Prompt Template (Alpaca)
### Instruction:
<prompt> (without the <>)
### Response:
🦒 Colab
| Link | Info - Model Name |
|---|---|
 |
MixTAO-7Bx2-MoE-v8.1 |
| mixtao-7bx2-moe-v8.1.Q4_K_M.gguf | GGUF of MixTAO-7Bx2-MoE-v8.1 Only Q4_K_M in https://huggingface.co/zhengr/MixTAO-7Bx2-MoE-v8.1-GGUF |
| Demo Space | https://huggingface.co/spaces/zhengr/MixTAO-7Bx2-MoE-v8.1/ |
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 77.50 |
| AI2 Reasoning Challenge (25-Shot) | 73.81 |
| HellaSwag (10-Shot) | 89.22 |
| MMLU (5-Shot) | 64.92 |
| TruthfulQA (0-shot) | 78.57 |
| Winogrande (5-shot) | 87.37 |
| GSM8k (5-shot) | 71.11 |
- Downloads last month
- 10,284
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for mixtao/MixTAO-7Bx2-MoE-v8.1
Spaces using mixtao/MixTAO-7Bx2-MoE-v8.1 3
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard73.810
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard89.220
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.920
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard78.570
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard87.370
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard71.110