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Med-PaLM 🌴🔬

The open source implementation of the Multi-Modality model from the research paper "Towards Generalist Biomedical AI"

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Med palm

🚀 Getting Started

pip install MedPalm

🧪 How to Use

import torch
from med_palm import MedPalm

# Kick-start the model
model = MedPalm()

# Let's get some tokenized inputs going
text_tokens = torch.tensor([[1, 2, 3, 4, 5]])  # Just an example! Use your own data.
images = torch.randn(1, 3, 224, 224)  # This too!

output = model(text_tokens, images)

print(output)

📝 Note: Modify the examples to suit your data and project needs.

📚 Datasets

🏛️ System Architecture

Med-PaLM is here to be the bridge 🌉 between the vast world of medical data types. From text 📜 to images 🖼️ and even genomic data 🧬, we've got you covered!

Our superstar? A massive multimodal generative model! 🌟 Trained on the swanky MultiMedBench, it's geared to tackle diverse tasks like medical Q&A, mammography interpretation, and even genomic variant calling!

💼 Commercial Use-Cases

Med-PaLM isn't just fun, it's super useful! 🛍️

  • Clinical Diagnostics: Combining medical imaging, patient tales 📖, and genes, we're aiming for top-notch diagnostic solutions.

  • Healthcare Research: Dive deep into diverse datasets and discover something new with Med-PaLM by your side! 🤿

  • Telemedicine: Quick, reliable, and remote! 🌍 Med-PaLM's here to revolutionize telehealth.

Contributing to Med Palm 🤖🌟

First off, big high fives 🙌 and thank you for considering a contribution to Med Palm! Your help and enthusiasm can truly elevate this project. Whether you're fixing bugs 🐛, adding features 🎁, or just providing feedback, every bit matters! Here's a step-by-step guide to make your contribution journey smooth:

1. Set the Stage 🎬

Fork the Repository: Before you dive in, create a fork of the Med Palm repository. This gives you your own workspace where you can make changes without affecting the main project.

  1. Go to the top right corner of the Med Palm repo.
  2. Click on the "Fork" button.

Boom! You now have a copy on your GitHub account.

2. Clone & Set Up 🚀

Clone Your Fork:

git clone https://github.com/kyegomez/Med-PaLM.git
cd Med-PaLM

Connect with the Main Repo: To fetch updates from the main Med Palm repository, set it up as a remote:

git remote add upstream https://github.com/kyegomez/Med-PaLM.git

3. Make Your Magic ✨

Create a new branch for your feature, bugfix, or whatever you're looking to contribute:

git checkout -b feature/my-awesome-feature

Now, dive into the code and sprinkle your magic!

4. Stay Updated 🔄

While you're working, the main Med Palm repository might have updates. Keep your local copy in sync:

git fetch upstream
git merge upstream/main

5. Share Your Brilliance 🎁

Once you've made your changes:

  1. Stage & Commit:

    git add .
    git commit -m "Add my awesome feature"
  2. Push to Your Fork:

    git push origin feature/my-awesome-feature
  3. Create a Pull Request: Head back to your fork on GitHub, and you'll see a "New Pull Request" button. Click on it!

6. The Review Dance 💃🕺

Once your PR is submitted, our team will review it. They might have questions or feedback. Stay engaged, discuss, and make any needed changes. Collaboration is key! 🤝

7. Celebrate 🎉

After review and any necessary tweaks, your contribution will be merged. Pat yourself on the back and celebrate! 🎊

8. Spread the Word 📢

Share about your contribution with your network. The more the merrier! Plus, it feels good to show off a bit, right? 😉

Remember, every contribution, no matter how small or large, is valued and appreciated. It's the collective effort that makes open-source so vibrant and impactful. Thanks for being a part of the Med Palm adventure! 🌟🚀


📜 License

Med-PaLM's chillin' under the MIT license. Check out the details here.

🎉 A Big Thank You!

A thunderous applause 👏 for the amazing clinicians and data wizards who've made Med-PaLM what it is today. We're on a mission to reshape healthcare, and every bit of your expertise has been invaluable!

So, let's dive into the world of biomedicine with Med-PaLM! 🎈🥳

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