| 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() |
