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  - entity recognition
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  - NER
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  - named entity recognition
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- - ' zero shot'
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  - zero-shot
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  ---
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- NuZero - is the family of Zero-Shot Entity Recognition models inspired by [GLiNER](https://huggingface.co/papers/2311.08526)
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  NuZero span is a more powerful version of GLiNER-large-v2.1, surpassing it by 4% on average, and is trained on the diverse internal dataset tailored for real-life use cases.
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  <p align="center">
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  <img src="zero_shot_performance_span.png">
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- </p>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - entity recognition
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  - NER
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  - named entity recognition
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+ - zero shot
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  - zero-shot
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  ---
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+ NuZero - is the family of Zero-Shot Entity Recognition models inspired by [GLiNER](https://huggingface.co/papers/2311.08526) and built with insights we gathered throughout our work on [NuNER](https://arxiv.org/abs/2402.15343).
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  NuZero span is a more powerful version of GLiNER-large-v2.1, surpassing it by 4% on average, and is trained on the diverse internal dataset tailored for real-life use cases.
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  <p align="center">
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  <img src="zero_shot_performance_span.png">
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+ </p>
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+
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+ ## Installation & Usage
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+ ```
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+ !pip install gliner
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+ ```
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+ ```python
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+ from gliner import GLiNER
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+
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+ model = GLiNER.from_pretrained("numind/NuZero_span")
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+ text = """
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+
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+ """
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+ labels = ["person", "award", "date", "competitions", "teams"]
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+
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+ entities = model.predict_entities(text, labels)
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+
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+ for entity in entities:
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+ print(entity["text"], "=>", entity["label"])
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+ ```
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+
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+ ## Fine-tuning
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+
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+
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+
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+