README.md

---
license: apache-2.0
tags:
- mistral
- pretrained
model-index:
- name: Mistral-11B-v0.1
  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: 59.56
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Undi95/Mistral-11B-v0.1
      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: 81.17
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Undi95/Mistral-11B-v0.1
      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: 63.56
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Undi95/Mistral-11B-v0.1
      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: 40.67
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Undi95/Mistral-11B-v0.1
      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: 76.64
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Undi95/Mistral-11B-v0.1
      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: 26.69
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Undi95/Mistral-11B-v0.1
      name: Open LLM Leaderboard
---

This is Mistral, but in 11B.

I took layers of the original Mistral-7B, and duplicated some layer, this is the first frankeinstein method that I found "acceptable" to expend Mistral.

It seems that the first 8 layers of the model is very important, having duplicate of those layers in the model make me think it confuse the model.

UPDATE: Forced mergekit to output bfloat16 file, should be the same thing, but since the base model is bfloat16, wanted it to stay bf16 like the OG model. Even if it was written bfloat16 in the config file earlier, it was float16.

<!-- description start -->
## Description

This repo contains fp16 files of Mistral-11B-v0.1.

<!-- description end -->
<!-- description start -->
## Model used

- [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1/)

<!-- description end -->
<!-- prompt-template start -->
## Prompt template: Alpaca

```
Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:

```

## The secret sauce

```
slices:
  - sources:
    - model: mistralai/Mistral-7B-v0.1
      layer_range: [0, 24]
  - sources:
    - model: mistralai/Mistral-7B-v0.1
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
```


Special thanks to Sushi.

If you want to support me, you can [here](https://ko-fi.com/undiai).
# [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_Undi95__Mistral-11B-v0.1)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |58.05|
|AI2 Reasoning Challenge (25-Shot)|59.56|
|HellaSwag (10-Shot)              |81.17|
|MMLU (5-Shot)                    |63.56|
|TruthfulQA (0-shot)              |40.67|
|Winogrande (5-shot)              |76.64|
|GSM8k (5-shot)                   |26.69|