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@@ -33,6 +33,23 @@ library_name: transformers
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  # Multilingual E5 for Document Classification (DocLayNet)
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  This model is a fine-tuned version of intfloat/multilingual-e5-large for document text classification based on the DocLayNet dataset.
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  ## Model description
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  - Base model: intfloat/multilingual-e5-large
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  - Task: Document text classification
@@ -70,19 +87,4 @@ hyperparameters:
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  'scheduler': 'cosine_with_warmup'
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  }
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  ```
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- ## Evaluation results
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- Test Loss: 0.5192, Test Acc: 0.9719
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-
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-
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- ## Usage:
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-
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- ```python
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- # Use a pipeline as a high-level helper
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- from transformers import pipeline
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-
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- pipe = pipeline("text-classification", model="kaixkhazaki/multilingual-e5-doclaynet")
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-
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- prediction = pipe("This is some text from a financial report")
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- print(prediction)
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- ```
 
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  # Multilingual E5 for Document Classification (DocLayNet)
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  This model is a fine-tuned version of intfloat/multilingual-e5-large for document text classification based on the DocLayNet dataset.
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+ ## Evaluation results
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+
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+ - Test Loss: 0.5192, Test Acc: 0.9719
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+
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+ ## Usage:
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+
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+ ```python
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+
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+ # Use a pipeline as a high-level helper
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+ from transformers import pipeline
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+
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+ pipe = pipeline("text-classification", model="kaixkhazaki/multilingual-e5-doclaynet")
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+
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+ prediction = pipe("This is some text from a financial report")
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+ print(prediction)
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+ ```
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+
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  ## Model description
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  - Base model: intfloat/multilingual-e5-large
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  - Task: Document text classification
 
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  'scheduler': 'cosine_with_warmup'
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  }
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  ```
 
 
 
 
 
 
 
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