📐 AI Math Equation Solver: Your Step-by-Step Solution Companion

Hello Hugging Face community! 👋 I'm excited to share my latest Space: the AI Math Equation Solver!

🔍 What does it do?

This Space uses the power of AI to solve math problems from images. Simply upload a picture of a math equation or problem, and the AI will provide a detailed, step-by-step solution. It's perfect for students, teachers, or anyone looking to understand complex mathematical concepts better.

🧠 How does it work?

- Backend: Utilizes the microsoft/Phi-3.5-vision-instruct model for image understanding and mathematical reasoning.
- Frontend: Built with Gradio for a clean, user-friendly interface.
- Features:
- Image upload for math problems
- Detailed step-by-step solutions
- Example problems to try instantly

🚀 Try it out!
sagar007/phi-vision-math-assistant


Visit the Space here: [Insert your Hugging Face Space URL]

💡 Use cases:

- Students: Check your work or get help with homework
- Teachers: Create detailed solution guides quickly
- Tutors: Explain complex problems more effectively
- Self-learners: Understand new mathematical concepts

🛠 Technical Details:

- Model: microsoft/Phi-3.5-vision-instruct
- Libraries: transformers, Gradio, PyTorch
- Optimizations: Uses Flash Attention for improved performance

🤝 Contribute:

This is an open project, and I welcome contributions! Whether it's improving the model, enhancing the UI, or adding new features, feel free to fork the project and submit your pull requests.

📣 Feedback:

I'd love to hear your thoughts! How are you using this Space? Any suggestions for improvements? Let me know in the comments below.

Happy problem-solving! 🎉

#MachineLearning #AI #Mathematics #Education #HuggingFace

safetensors
v0.4.4
Provides functions to read and write safetensors which aim to be safer than their PyTorch counterpart. The format is 8 bytes which is an unsized int, being the size of a JSON header, the JSON header refers the dtype the shape and data_offsets which are the offsets for the values in the rest of the file.
Installation
Pip
You can install safetensors via the pip manager:

pip install safetensors
From source
For the sources, you need Rust

# Install Rust
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
# Make sure it's up to date and using stable channel
rustup update
git clone https://github.com/huggingface/safetensors
cd safetensors/bindings/python
pip install setuptools_rust
pip install -e .
Getting started
import torch
from safetensors import safe_open
from safetensors.torch import save_file

tensors = {
"weight1": torch.zeros((1024, 1024)),
"weight2": torch.zeros((1024, 1024))
}
save_file(tensors, "model.safetensors")

tensors = {}
with safe_open("model.safetensors", framework="pt", device="cpu") as f:
for key in f.keys():
tensors[key] = f.get_tensor(key)
Python documentation
#tensorflow #pytorch #huggingface #tensors #safetensors

GitHub

GitHub - huggingface/safetensors: Simple, safe way to store and distribute tensors

Simple, safe way to store and distribute tensors. Contribute to huggingface/safetensors development by creating an account on GitHub.