---
language:
- en
library_name: transformers
pipeline_tag: text-generation
datasets:
- jondurbin/airoboros-2.2
- Open-Orca/OpenOrca
- garage-bAInd/Open-Platypus
- WizardLM/WizardLM_evol_instruct_V2_196k
- TokenBender/python_eval_instruct_51k
tags:
- code
license: apache-2.0
model-index:
- name: SpeechlessCoder
  results:
  - task:
      type: text-generation
    dataset:
      type: openai_humaneval
      name: HumanEval
    metrics:
    - name: pass@1
      type: pass@1
      value: 
      verified: false
---

<p><h1> speechless-instruct-mistral-7b-v0.2  </h1></p>

Code: https://github.com/uukuguy/speechless

Use the following dataset to fine-tune mistralai/Mistral-7B-v0.2 in order to improve the model's reasoning and planning abilities.

Total 201,981 samples.
- jondurbin/airoboros-2.2: Filter categories related to coding, reasoning and planning. 23,462 samples.
- Open-Orca/OpenOrca: Filter the 'cot' category in 1M GPT4 dataset. 74,440 samples.
- garage-bAInd/Open-Platypus: 100%, 24,926 samples.
- WizardLM/WizardLM_evol_instruct_V2_196k: Coding coversation part. 30,185 samples
- TokenBender/python_eval_instruct_51k: “python” in output .40,309 samples
- Spider: 8,659 samples

## How to Prompt the Model
This model accepts the Alpaca instruction format.

For example:
```
You are an intelligent programming assistant.

### Instruction:
Implement a linked list in C++

### Response:
```

## HumanEval

| Metric | Value |
| --- | --- |
| humaneval-python |  |

Big Code Models Leaderboard](https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard)

CodeLlama-34B-Python: 53.29

CodeLlama-34B-Instruct: 50.79

CodeLlama-13B-Instruct: 50.6

CodeLlama-34B: 45.11

CodeLlama-13B-Python: 42.89

CodeLlama-13B: 35.07


[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)

| Metric | Value |
| --- | --- |
| ARC | 58.79 |
| HellaSwag | 81.89 |
| MMLU | 61.27 |
| TruthfulQA | 49.85 |
| Winoground | 78.22 |
| GSM8K | 56.33 |
| Average | 64.39 |