import gradio as gr | |
from transformers.utils import logging | |
logging.set_verbosity_error() | |
from sentence_transformers import SentenceTransformer | |
from sentence_transformers import util | |
def compare(input): | |
lines = input.splitlines() | |
embeddings1 = model.encode(lines[0], convert_to_tensor=True) | |
embeddings2 = model.encode(lines[1], convert_to_tensor=True) | |
cosine_scores = util.cos_sim(embeddings1, embeddings2) | |
return "Score: {:.4f} \t\t {} \t\t {}".format(cosine_scores[0][0], lines[0], lines[1]) | |
model = SentenceTransformer("all-MiniLM-L6-v2") | |
demo = gr.Interface(fn=compare, inputs="textarea", outputs="text") | |
demo.launch() | |
gr.close_all() |