| import gradio as gr | |
| from sentence_transformers import SentenceTransformer | |
| model = SentenceTransformer("Auparima/thaifood-embed") | |
| def embed_text(text): | |
| emb = model.encode(text) | |
| return str(emb[:10]) | |
| demo = gr.Interface( | |
| fn=embed_text, | |
| inputs="text", | |
| outputs="text", | |
| title="ThaiFood Embedding Model" | |
| ) | |
| demo.launch() |