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Expand Up @@ -11,19 +11,17 @@ pinned: false

# Feel

This is a project to create a continuous training application.
Platform developed at MIT in collaboration with the HuggingFace platform and with inputs from IBM, Cohere, KAIST, and other independent collaborators. Aimed at improving performance of existing open source Large Language Models through real-time human feedback loop.

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.
This repository hosts the development of a novel automated RLHF platform where the community can provide feedback which is then immediately integrated and used to improve the models in real time. 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.
A community-driven project to improve multilingual capabilities in Large Language Models (LLMs). Leverages feedback from users and automated RLHF pipelines to continuously improve model performance.

## Why Feel?
## 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.
FeeL = Feedback Loop. It 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

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