---
license: apache-2.0
datasets:
- the_pile
- guanaco/guanaco
language:
- en
---

# Model Card for Cerebras 1.3b Dollyfied.

This is a finetuned model of Cerebras 1.3b model. using DataBricksLabs Dolly Framework

## Model Details

### Model Description

This is a finetuned version of cerebras' 1.3Billion paramater model that has been trained to follow instructions.

It was accomplished using DataBricks Dolly training tools, and was trained for 2 epochs.

- **Developed by:** Finetuned by Corianas (me) using open source tools
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** EN
- **License:** cc-by-nc-4.0
- **Finetuned from model:** https://huggingface.co/cerebras/Cerebras-GPT-111m
- **Finetuned using:** https://www.databricks.com/blog/2023/03/24/hello-dolly-democratizing-magic-chatgpt-open-models.html

## Uses

This is a simple GPT chatbot that has been finetuned to understand instructions.
Its knowledge about facts about the world is should be considered suspect at best.

### Direct Use

If you have a use you put it to, Please let me know.

[More Information Needed]

### Downstream Use [optional]

<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->

[More Information Needed]

### Out-of-Scope Use

Any form of use where any form of accuracy is needed.
FOR THE LOVE OF GOD DO NOT FOLLOW MEDICAL ADVICE FROM THIS.
or financial advice.

[More Information Needed]

## Bias, Risks, and Limitations

Limitations... Yes, I am sure there are so so many.


## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** 8xA100s (accomplished while I was downloading the model I was actually training.)
- **Minutes used:** 17
- **Cloud Provider:** LambdaGPU
- **Compute Region:** USA
- **Carbon Emitted:** [More Information Needed]

# [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_Corianas__Quokka_1.3b)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 27.1   |
| ARC (25-shot)         | 27.73          |
| HellaSwag (10-shot)   | 37.91    |
| MMLU (5-shot)         | 26.66         |
| TruthfulQA (0-shot)   | 40.14   |
| Winogrande (5-shot)   | 52.72   |
| GSM8K (5-shot)        | 0.0        |
| DROP (3-shot)         | 4.54         |