---
tags:
- autotrain
- text-generation
datasets:
- neovalle/H4rmony
language:
- en
library_name: transformers
license: mit
---

# Model Card for Model neovalle/H4rmoniousBreeze

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aac16fd4a402e8dce11ebe/jTG5tI90phw8bJKvkJaHQ.jpeg)

## Model Details

### Model Description

This is model is a version of HuggingFaceH4/zephyr-7b-beta fine-tuned via Autotrain Reward Model, using the H4rmony dataset, which aims 
to better align the model with ecological values through the use of ecolinguistics principles.

- **Developed by:** Jorge Vallego 
- **Funded by :** Neovalle Ltd.
- **Shared by :** airesearch@neovalle.co.uk
- **Model type:** mistral 
- **Language(s) (NLP):** Primarily English
- **License:** MIT
- **Finetuned from model:** HuggingFaceH4/zephyr-7b-beta


## Uses

Intended as PoC to show the effects of H4rmony dataset.

### Direct Use

For testing purposes to gain insight in order to help with the continous improvement of the H4rmony dataset.

### Downstream Use

Its direct use in applications is not recommended as this model is under testing for a specific task only (Ecological Alignment)

### Out-of-Scope Use

Not meant to be used other than testing and evaluation of the H4rmony dataset and ecological alignment.

## Bias, Risks, and Limitations

This model might produce biased completions already existing in the base model, and others unintentionally introduced during fine-tuning.

## How to Get Started with the Model

It can be loaded and run in a Colab instance with High RAM.
Code to load base and finetuned models to compare outputs:

https://github.com/Neovalle/H4rmony/blob/main/H4rmoniousBreeze.ipynb

## Training Details

Autotrained reward model 

### Training Data

H4rmony Dataset - https://huggingface.co/datasets/neovalle/H4rmony