fix: updated readme

README.md

@@ -1,73 +1,12 @@
-<div align="center">
-  <a href="https://ibb.co/gTkPrng">
-    <img src="https://i.ibb.co/FXYXZfD/Nebul-OS-logo.png" alt="Nebul-OS-logo" border="0">
-  </a>
-</div>
-
-# NebulOS: Fair, green AI. For Real 🌿
-Welcome to the GitHub repository of the 18th ASP cycle coolest project! 🚀
-
-With NebulOS, we push the boundaries AI adoption, focusing on how to design architectures tailored for the hardware on which they run.
-During this wonderful journey, we counted on the support of the amazing people at [Nebuly](https://www.nebuly.com/) (8.3k 🌟 on GitHub), as well the guidance and help by Prof. [Barbara Caputo](linkedin.com/in/barbara-caputo-a610201a7/?originalSubdomain=it) (Politecnico di Torino, Top50 Universities world-wide), and Prof. [Stefana Maja Broadbent](https://www.linkedin.com/in/stefanabroadbent/?originalSubdomain=uk) (Politecnico di Milano, Top20 Universities world-wide).
-
-Give us a star to show your support for the project ⭐
-You can find an extended abstract of this project [here](https://sites.google.com/view/nebulos)
-
-## Foreword 📝
-### Alta Scuola Politecnica (ASP)
-Alta Scuola Politecnica (more [here](https://www.asp-poli.it/)) is the **joint honors program** of Italy's best technical universities, Politecnico di Milano ([18th world-wide, QS Rankings](https://www.topuniversities.com/university-rankings/university-subject-rankings/2023/engineering-technology?&page=1)) and Politecnico di Torino ([45th world-wide, QS Rankings](https://www.topuniversities.com/university-rankings/university-subject-rankings/2023/engineering-technology?&page=1)). 
-Each year, 90 students from Politecnico di Milano and 60 from Politecnico di Torino are selected from a highly competitive pool and those who succeed receive free tuition for their MSc in exchange for ~1.5 years working as **student consultants** with a partner company for an industrial project.
-
-The project we present has been carried out with the invaluable support of folks at [Nebuly](https://www.nebuly.com/), the company behind the very well-known [`nebullvm`](https://github.com/nebuly-ai/nebuly/tree/main/optimization/nebullvm) open-source AI-acceleration library 🚀
-
-Alongside them, we have developed a stable and reliable AI-acceleration tool that capable of designing just the right network for each specific target device. 
-With this, we propose a new answer to an old Deep Learning question: how to bring large models to tiny devices. **Screw forcing a circle in a square-hole**: we feel like we are the trouble-makers here, *better to change the model from the ground up!*
-
-## Contributions 🌟
-NebulOS takes a step further by adopting actual hardware-aware metrics (such as the architectures' energy consumption 🌿) to perform the automated design of Deep Neural Architectures.
-
-## How to Reproduce the Results 💻
-1. **Clone the Repository**: `git clone https://github.com/fracapuano/NebulOS.git`
-2. **Install Dependencies**: 
-After having made sure you have a working version of `conda` on your machine (you can double-check running the command `conda` in your terminal), go ahead:
-- Creating the environment (this code has been fully tested for Python 3.10)
-```bash
-conda create -n nebulosenv python=3.10 -y
-```
-- Activating the environment
-```bash
-conda activate nebulosenv
-```
-- Installing the (very minimal) necessary requirements
-```bash
-pip install -r requirements.txt
-```
-3. **Run the Code**: Use the provided scripts and guidelines in the repository.
-To reproduce our results you can simply run the following command:
-```bash
-python nas.py
-```
-
-To specialize your search, you can select multiple arguments. You may select those of interest to you using Python args. To see all args available you run:
-
-```bash
-python nas.py --help
-```
-
-For instance, you can specify a search for an NVIDIA Jetson Nano device on ImageNet16-120 by running:
-```bash
-python nas.py --device edgegpu --dataset ImageNet16-120
-```
-## Live-demo ⚡
-Our live demo is currently hosted as an Hugging Face space. You can find it at [spaces/fracapuano/NebulOS](https://huggingface.co/spaces/fracapuano/NebulOS)
-
-## Next modules and roadmap
-We are actively working on obtaining the next results.
-
-- [ ] Extending this work to deal with Transformer networks in NLP.
-- [ ] Bring actual AI Optimization to LLMs.
-
-## Conclusions 🌍
-We really hyped up about NebulOS because we feel it is way more than an extension; it's a revolution in the field of Green-AI. This project stays as a testament of our commitment toward truly sustainable AI, and by adopting actual hardware-aware metrics, we are making a tangible difference in the world of Deep Neural Architectures. 
-
-Join us in this journey towards a greener future! Help us keep AI beneficial to all. This time, for real.
+---
+title: {NebulOS}
+emoji: {🌿}
+colorFrom: {#FCEEB5}
+colorTo: {#A7C7E7}
+sdk: {streamlit}
+sdk_version: {1.25.0}
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference