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| # Workaround to install the lib without "setup.py" | |
| import sys | |
| from git import Repo | |
| Repo.clone_from("https://github.com/dimitreOliveira/hub.git", "./hub") | |
| sys.path.append("/hub") | |
| import gradio as gr | |
| from hub.tensorflow_hub.hf_utils import pull_from_hub | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| model = pull_from_hub(repo_id="Dimitre/universal-sentence-encoder") | |
| def get_similarity(sentence_a, sentence_b): | |
| embed_a = model([sentence_a]) | |
| embed_b = model([sentence_b]) | |
| similarity = cosine_similarity(embed_a, embed_b)[0][0] | |
| return f'The similarity score between sentence A and sentence B is: "{similarity:.2f}"' | |
| iface = gr.Interface(fn=get_similarity, | |
| title="Sentence similarity", | |
| description="Measure the similarity between sentences using universal-sentence-encoder", | |
| inputs=[gr.Textbox(lines=2, placeholder="Sentence A here...", label="Sentence A"), | |
| gr.Textbox(lines=2, placeholder="Sentence B here...", label="Sentence B")], | |
| outputs="text", | |
| examples=[["Hello! This is a random sentence", "Hello! This is a slightly different random sentence"]]) | |
| iface.launch() |