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@@ -13,4 +13,6 @@ This model is designed for Named Entity Recognition (NER) tasks, specifically ta
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  - **Inference Time:** The model runs on CPUs, with an inference time of 0.01 seconds on a GPU. Performance on a CPU will vary depending on the specific hardware configuration.
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  ## Try It Out
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- You can test the model directly in your browser through the following Hugging Face Spaces link: [https://huggingface.co/spaces/DeepMount00/universal_ner](https://huggingface.co/spaces/DeepMount00/universal_ner).
 
 
 
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  - **Inference Time:** The model runs on CPUs, with an inference time of 0.01 seconds on a GPU. Performance on a CPU will vary depending on the specific hardware configuration.
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  ## Try It Out
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+ You can test the model directly in your browser through the following Hugging Face Spaces link: [https://huggingface.co/spaces/DeepMount00/universal_ner](https://huggingface.co/spaces/DeepMount00/universal_ner).
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+ It's important to note that **this model is universal and operates across all domains**. However, if you are seeking performance metrics close to a 98/99% F1 score for a specific domain, you are encouraged to reach out via email to Michele Montebovi at montebovi.michele@gmail.com. This direct contact allows for the possibility of customizing the model to achieve enhanced performance tailored to your unique entity recognition requirements in the Italian language.