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@@ -18,7 +18,7 @@ You can test the model directly in your browser through the following Hugging Fa
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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 90/99% 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.
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  # Installation
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- To use this model, you must download the GLiNER repository and install its dependencies:
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  ```
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  !git clone https://github.com/urchade/GLiNER.git
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  ```
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  # Usage
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- Once you've downloaded the GLiNER repository, you can import the GLiNER class from the model file. You can then load this model using GLiNER.from_pretrained and predict entities with predict_entities.
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  ```python
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  from model import GLiNER
 
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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 90/99% 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.
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  # Installation
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+ To use this model, you must download the GLiNER repository and install its dependencies!!:
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  ```
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  !git clone https://github.com/urchade/GLiNER.git
 
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  ```
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  # Usage
 
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  ```python
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  from model import GLiNER