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Browse files- .gitignore +1 -0
- app.py +29 -0
- requirements.txt +1 -0
.gitignore
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.idea
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app.py
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from typing import List
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import gradio as gr
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import spaces
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer("nomic-ai/nomic-embed-text-v1", trust_remote_code=True, device='cuda')
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@spaces.GPU
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def embed(documents: List[str]):
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embeddings = []
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for document in documents:
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embeddings.append(model.encode(document))
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return embeddings
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with gr.Blocks() as app:
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# Create an input text box
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text_input = gr.Textbox(label="Enter text to embed")
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# Create an output component to display the embedding
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output = gr.JSON(label="Text Embedding")
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# When the input text is submitted, call the embedding function and display the output
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text_input.submit(embed, inputs=text_input, outputs=output)
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if __name__ == '__main__':
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app.queue().launch(server_name="0.0.0.0", show_error=True, server_port=7860)
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requirements.txt
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sentence_transformers==2.6.0
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