Update README with installable gliner; add library_name

README.md

@@ -2,6 +2,7 @@
 language:
 - it
 pipeline_tag: token-classification
+library_name: gliner
 ---
 
 # Universal NER for Italian (Zero-Shot)
@@ -18,18 +19,16 @@ You can test the model directly in your browser through the following Hugging Fa
 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 [email protected]. 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.
 
 # Installation
-To use this model, you must download the GLiNER repository and install its dependencies!!:
+To use this model, you must download the GLiNER project:
 
 ```
-!git clone https://github.com/urchade/GLiNER.git
-%cd GLiNER
-!pip install -r requirements.txt
+!pip install gliner
 ```
 
 # Usage
 
 ```python
-from model import GLiNER
+from gliner import GLiNER
 
 model = GLiNER.from_pretrained("DeepMount00/universal_ner_ita")