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import gradio as gr
from transformers import AutoModel, AutoTokenizer
# Load a small CPU model for text to vector processing
model_name = "sentence-transformers/all-MiniLM-L6-v2"
model = AutoModel.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
def text_to_vector(text):
"""
Converts text to a vector representation using a pre-trained model.
"""
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
vector = outputs.pooler_output.detach().numpy()[0]
# Convert the vector to a string representation for display
vector_str = ", ".join([str(x) for x in vector])
return vector_str
demo = gr.Interface(
fn=text_to_vector,
inputs=gr.Textbox(label="Enter text"),
outputs=gr.Textbox(label="Text Vector"),
title="Text to Vector",
description="This demo uses a small CPU model to convert text to vector."
)
demo.launch()
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