# MelloGPT
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   <img width="150" height="150" src="https://raw.githubusercontent.com/steve-cse/mello/master/public/logo.png" alt="Logo">
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**NOTE: This model should not be regarded as a replacement for professional mental health assistance. It is essential to seek support from qualified professionals for personalized and appropriate care.**

A fine tuned version of [Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on [counsel-chat](https://huggingface.co/datasets/nbertagnolli/counsel-chat) dataset for mental health counseling conversations.
## Motivation
In an era where mental health support is of paramount importance, A large language
model fine-tuned on mental health counseling conversations stands as a pioneering solution. This
approach aims to elevate natural language understanding and generation within the realm of mental
health support. Leveraging a diverse dataset of anonymized counseling sessions, the model has
been trained to recognize and respond to a wide range of mental health concerns, including anxiety,
depression, stress, and more. The fine-tuning process incorporates ethical considerations, privacy
concerns, and sensitivity to the nuances of mental health conversations. The resulting model will
demonstrate an intricate understanding of mental health issues and provide empathetic and
supportive responses, offering a valuable tool for individuals seeking guidance, mental health
professionals, and the broader healthcare community.
## Prompt Template
```
<s>[INST] {prompt} [/INST]
```
## Quantized Model 
The quantized model can be found [here](https://huggingface.co/TheBloke/MelloGPT-GGUF). Thanks to [@TheBloke](https://huggingface.co/TheBloke).

## Contributions
This project is open for contributions. Feel free to use the community tab.

## Inspiration
This project was inspired by the project(s) listed below:

[companion_cube](https://huggingface.co/KnutJaegersberg/companion_cube_ggml) by [@KnutJaegersberg](https://huggingface.co/KnutJaegersberg)

## Credits
This is my first attempt at fine-tuning a large language model. It wouldn't be possible without [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) and [Runpod](runpod.io). The axolotl config file can be found [here](https://github.com/steve-cse/mello/blob/master/mello.yml).

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
{"license": "mit", "datasets": ["nbertagnolli/counsel-chat"]}
transformers pytorch mistral text-generation conversational dataset:nbertagnolli/counsel-chat license:mit autotrain_compatible endpoints_compatible has_space text-generation-inference region:us