README.md

---
license: apache-2.0
tags:
- moe
model-index:
- name: MixTAO-7Bx2-MoE-v8.1
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 73.81
      name: normalized accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=zhengr/MixTAO-7Bx2-MoE-v8.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 89.22
      name: normalized accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=zhengr/MixTAO-7Bx2-MoE-v8.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.92
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=zhengr/MixTAO-7Bx2-MoE-v8.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 78.57
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=zhengr/MixTAO-7Bx2-MoE-v8.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 87.37
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=zhengr/MixTAO-7Bx2-MoE-v8.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 71.11
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=zhengr/MixTAO-7Bx2-MoE-v8.1
      name: Open LLM Leaderboard
---

# 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 |
| --- | --- |
|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1y2XmAGrQvVfbgtimTsCBO3tem735q7HZ?usp=sharing) | MixTAO-7Bx2-MoE-v8.1 |
|[mixtao-7bx2-moe-v8.1.Q4_K_M.gguf](https://huggingface.co/zhengr/MixTAO-7Bx2-MoE-v8.1-GGUF/resolve/main/mixtao-7bx2-moe-v8.1.Q4_K_M.gguf) | GGUF of MixTAO-7Bx2-MoE-v8.1 <br> 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](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_zhengr__MixTAO-7Bx2-MoE-v8.1)

|             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|