Spaces:
Runtime error
Runtime error
| import gradio as gr | |
| import torch | |
| from sentence_transformers import SentenceTransformer | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| model = SentenceTransformer( | |
| "sentence-transformers/sentence-t5-base", | |
| device="cuda" if torch.cuda.is_available() else "cpu" | |
| ) | |
| def get_metrics(vec1, vec2): | |
| sim = float(cosine_similarity(vec1, vec2)[0][0]) | |
| scs = abs((sim) ** 3) | |
| m = { | |
| "cosine_similarity": round(sim, 4), | |
| "scs": round(scs, 4) | |
| } | |
| return m | |
| def compute(text1, text2): | |
| texts = [text1, text2] | |
| embeddings = model.encode( | |
| texts, | |
| show_progress_bar=False, | |
| convert_to_numpy=True, | |
| normalize_embeddings=True, | |
| ) | |
| return get_metrics(embeddings[0].reshape(1, -1), embeddings[1].reshape(1, -1)) | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| text1 = gr.Textbox(label="Enter Text 1") | |
| text2 = gr.Textbox(label="Enter Text 2") | |
| with gr.Column(): | |
| submit_btn = gr.Button("Submit") | |
| output = gr.JSON( | |
| label="Score", | |
| ) | |
| # # callback --- | |
| submit_btn.click( | |
| fn=compute, | |
| inputs=[text1, text2], | |
| outputs=output | |
| ) | |
| demo.launch() | |