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| title: Image2Wiki | |
| emoji: 🖼️ | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: docker | |
| pinned: false | |
| # Image2Wiki | |
| [](https://huggingface.co/spaces/letitbE/image2wiki) | |
| Image2Wiki is a service that generates Wikipedia-style articles based on an uploaded image. It uses a fine-tuned VisionEncoderDecoder model (`tuman/vit-rugpt2-image-captioning` with a LoRA adapter) to generate structured text (title, lead, sections, paragraphs) from images. | |
| ## Features | |
| - FastAPI based web service | |
| - Wikipedia-like UI for generated articles | |
| - Fine-tuned model for structured article generation | |
| ## Setup | |
| 1. Install dependencies: | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| 2. Run the service: | |
| ```bash | |
| uvicorn app.main:app --port 8013 --reload | |
| ``` | |
| ## Project Structure | |
| - `app/` - FastAPI application and UI templates | |
| - `adapted_best_embed2/` - Fine-tuned LoRA adapter weights | |
| - `collect_data.py` & `collect_data_async.py` - Scripts for collecting training data | |
| - `finetune.ipynb` - Notebook used for fine-tuning the model | |