| title | Feel |
|---|---|
| emoji | 🚀 |
| colorFrom | blue |
| colorTo | gray |
| sdk | gradio |
| sdk_version | 5.10.0 |
| app_file | app/app.py |
| pinned | false |
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.
A community-driven project to improve Multilingual Vision-Language Models (VLMs). Leverages feedback from users and automated RLHF pipelines to continuously improve model performance.
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.
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
The repository uses uv for managing virtual environments. To install uv, go here. Create a virtual environment.
uv venv --python 3.11Activate the virtual environment
source .venv/bin/activateSync the dependencies
uv sync --all-groupsTo install the required dependencies, run the following commands:
uv sync --group mluv sync --group appFirst, add the remote
git remote add hf https://huggingface.co/spaces/feel-fl/open-human-feedback-chat
Push to the remote branch
git push hf main