Token Classification
GLiNER
PyTorch
multilingual
NER
GLiNER
information extraction
encoder
entity recognition
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@@ -72,11 +72,15 @@ European Championship => competitions
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  If you want to use flash attention or increase sequence length, please, check the following code:
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  ```python
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- model = GLiNER.from_pretrained("knowledgator/gliner-bi-llama-v1.0",
 
 
 
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  _attn_implementation = 'flash_attention_2',
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- max_len = 2048).to('cuda:0')
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  ```
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  If you have a large amount of entities and want to pre-embed them, please, refer to the following code snippet:
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  ```python
 
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  If you want to use flash attention or increase sequence length, please, check the following code:
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  ```python
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+ from gliner import GLiNER
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+ import torch
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+
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+ model = GLiNER.from_pretrained("knowledgator/gliner-qwen-1.5B-v1.0",
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  _attn_implementation = 'flash_attention_2',
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+ max_len = 2048).to('cuda:0', dtype=torch.float16)
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  ```
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+
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  If you have a large amount of entities and want to pre-embed them, please, refer to the following code snippet:
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  ```python