Spaces:
Sleeping
Sleeping
| title: AnalogyArcade | |
| emoji: 🏆 | |
| colorFrom: blue | |
| colorTo: yellow | |
| sdk: gradio | |
| sdk_version: 4.8.0 | |
| app_file: app.py | |
| pinned: false | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
| ## Information | |
| ### Database | |
| [ag_news]([https://huggingface.co/datasets/glue](https://huggingface.co/datasets/ag_news) | |
| This database uses a text with label format, with each label being an integer between 0 and 3, relating to the 4 main categories of the news: World (0), Sports (1), Business (2), Sci/Tech (3). | |
| I chose this one because of the larger variety of categories compared to sentiment databases, with the themes/categories theoretically being more closely related to analogies. I also chose ag_news because, as a news source, it should avoid slang and other potential hiccups that databases using tweets or general reviews will have. | |
| ### Pre-trained model | |
| [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) | |
| Because my focus is on using embeddings to evaluate analogies for the AnalogyArcade, I focused my model search for those in the sentence-transformers category, as they are readily made for embedding usage. I chose all-MiniLM-L6-v2 because of its high usage and good reviews: it is a well trained model but smaller and more efficient than its previous version. | |
| TESTING README UPDATE | |