| import gradio as gr | |
| from sentence_transformers import SentenceTransformer, util | |
| model_id = "sentence-transformers/multi-qa-mpnet-base-dot-v1" | |
| model = SentenceTransformer( | |
| model_id | |
| ) | |
| def launch(source_sentence, sentences): | |
| source = model.encode(source_sentence, convert_to_tensor=True) | |
| references = model.encode([e.strip() for e in sentences.split("|")], convert_to_tensor=True) | |
| return ",".join([str(e) for e in util.pytorch_cos_sim(source, references).flatten().tolist()]) | |
| iface = gr.Interface(launch, inputs=["text","text"], outputs="text") | |
| iface.launch() |