DeepMount00 tomaarsen HF staff commited on
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Update README with installable gliner; add library_name (#1)

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- Update README with installable gliner; add library_name (b8ac8a6f69cadeaa8a49663d341753fbcb19c363)


Co-authored-by: Tom Aarsen <[email protected]>

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  1. README.md +4 -5
README.md CHANGED
@@ -2,6 +2,7 @@
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  language:
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  - it
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  pipeline_tag: token-classification
 
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  ---
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  # Universal NER for Italian (Zero-Shot)
@@ -18,18 +19,16 @@ 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 [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.
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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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- %cd GLiNER
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- !pip install -r requirements.txt
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  ```
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  # Usage
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  ```python
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- from model import GLiNER
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  model = GLiNER.from_pretrained("DeepMount00/universal_ner_ita")
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  language:
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  - it
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  pipeline_tag: token-classification
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+ library_name: gliner
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  ---
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  # Universal NER for Italian (Zero-Shot)
 
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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 [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.
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  # Installation
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+ To use this model, you must download the GLiNER project:
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  ```
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+ !pip install gliner
 
 
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  ```
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  # Usage
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  ```python
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+ from gliner import GLiNER
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  model = GLiNER.from_pretrained("DeepMount00/universal_ner_ita")
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