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README.md
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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
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openvino
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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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## Benchmark
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Zero-shot performance (English):
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