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---
title: Que Ans
emoji: 🐨
colorFrom: yellow
colorTo: blue
sdk: gradio
sdk_version: 4.42.0
app_file: app.py
pinned: false
license: apache-2.0
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
# Image Question Answering with BLIP
Welcome to the Image Question Answering Space! This Hugging Face Space demonstrates a BLIP (Bootstrapped Language-Image Pretraining) model for answering questions about images. The application uses Gradio to provide an interactive web interface.
## Overview
This Space allows users to upload an image and ask a question about it. The BLIP model processes the image and question to generate an answer. The model has been deployed using Gradio for easy interaction.
## How to Use
Interact with the Model
- Upload an Image: Click on the upload button to select an image from your device.
- Ask a Question: Type your question about the image in the provided text box.
- Get the Answer: Click on the "Submit" button to see the model's response.
Model Details
- Model: BLIP (Bootstrapped Language-Image Pretraining)
- Framework: Transformers and Gradio
- Functionality: The model provides answers to questions based on the content of the uploaded image.
Example
1. Upload an Image: Example image of a cat.
2. Ask a Question: "Which animal is this?"
3. Response: The model will provide an answer based on the image content i.e cat.
API Access:
You can also use the API developed with Gradio for your own work. The API allows you to programmatically interact with the model.
About Gradio:
Gradio provides a simple way to create web interfaces for machine learning models. It enables easy sharing and interaction with models through a user-friendly web application.
Acknowledgments
- Hugging Face: For providing the Space platform and the BLIP model.
- Gradio: For the interactive web interface.
Feedback and Support
If you encounter any issues or have suggestions for improvement, please reach out through the Hugging Face discussion forums or file an issue on the [GitHub repository](https://github.com/avinash4002/image_qna).