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---
title: Feel
emoji: 🚀
colorFrom: blue
colorTo: gray
sdk: gradio
sdk_version: 5.8.0
app_file: app/app.py
pinned: false
---
# Feel
This is a project to create a continuous training application.
Platform being developed at MIT in collaboration with HuggingFace. Aimed at improving performance of existing Large Language Models through real-time human feedback loop.
This repository hosts the development of an automated RLHF platform for Hugging Face, where the community can provide real-time feedback on language models. The feedback is automatically integrated into an RLHF pipeline to continuously fine-tune and improve the models.
## What is Feel?
A community-driven project to improve Multilingual Vision-Language Models (VLMs). Leverages feedback from users and automated RLHF pipelines to continuously improve model performance.
## Why Feel?
Feel is a platform that enables the community to provide real-time feedback on language models. The feedback is automatically integrated into an RLHF pipeline to continuously fine-tune and improve the models.
## Repository Structure
The repository is organized as follows:
```
ml/ # Directory for machine learning code
├── README.md # Dataset schema and project structure
├── data/ # Directory for dataset files
├── models/ # Directory for model files
app/ # Directory for application code
├── app.py # Main application file
```
## Installation
The repository uses `uv` for managing virtual environments. To install `uv`, go [here](https://docs.astral.sh/uv/getting-started/installation/). Create a virtual environment.
```bash
uv venv --python 3.11
```
Activate the virtual environment
```bash
source .venv/bin/activate
```
Sync the dependencies
```bash
uv sync --all-groups
```
To install the required dependencies, run the following commands:
### ML Dependencies
```bash
uv sync --group ml
```
### App Dependencies
```bash
uv sync --group app
```
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