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@@ -41,13 +41,18 @@ pip install "torch>=2.1" "nncf>=2.7" "transformers>=4.40.0" "onnx<1.16.2" "optim
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  ```
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  This command will install, among others:
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  ```
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- tokenizers-0.20.3
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- transformers-4.46.3
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- huggingface-hub-0.26.3
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- openvino-tokenizers-2024.4.1.0.dev20240926
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- optimum-1.23.3
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- optimum-intel-1.20.1
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- openvino-2024.4.1.dev20240926-16618
 
 
 
 
 
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  ```
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@@ -143,6 +148,25 @@ console.print(f'Generated in {delta}')
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  ```
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  ## Benchmark
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  Zero-shot performance (English):
 
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  ```
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  This command will install, among others:
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  ```
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+ tokenizers==0.20.3
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+ torch==2.5.1+cpu
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+ transformers==4.46.3
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+ nncf==2.14.0
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+ numpy==2.1.3
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+ onnx==1.16.1
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+ openvino==2024.5.0
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+ openvino-genai==2024.5.0.0
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+ openvino-telemetry==2024.5.0
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+ openvino-tokenizers==2024.5.0.0
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+ optimum==1.23.3
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+ optimum-intel @ git+https://github.com/huggingface/optimum-intel.git@c454b0000279ac9801302d726fbbbc1152733315
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  ```
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  ```
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+ <p align="left">
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+ <img src="https://github.com/fabiomatricardi/NuExtract-1.5-openvino/raw/main/logo_long.png" style="width: 600; height: auto;">
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+ </p>
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+ ## An awesome Streamlit+OpenVINO interface [![Mentioned in Awesome OpenVINO](https://awesome.re/mentioned-badge-flat.svg)](https://github.com/openvinotoolkit/awesome-openvino)
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+ you can find the code in [my official GitHub repository](https://github.com/fabiomatricardi/NuExtract-1.5-openvino)
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+ You can clone the repo and use the downloaded files from this Hugging Face Model
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+ Running the streamlit app will give this:
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+ <p align="left">
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+ <img src="https://github.com/fabiomatricardi/NuExtract-1.5-openvino/raw/main/streamlitapp.png" style="width: 600; height: auto;">
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+ </p>
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+
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+ ---
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+
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  ## Benchmark
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  Zero-shot performance (English):