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  This model is a fine-tune checkpoint of [Yanzhu/bertweetfr-base](https://huggingface.co/Yanzhu/bertweetfr-base), fine-tuned on SST-2.
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  This model reaches an accuracy of 71% on the dev set.
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  In this dataset, given a tweet, the goal was to infer the underlying topic of the tweet by choosing from four topics classes:
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- -positif
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- -negatif
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- -neutre
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-
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- # Pipelining the Model
 
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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  This model is a fine-tune checkpoint of [Yanzhu/bertweetfr-base](https://huggingface.co/Yanzhu/bertweetfr-base), fine-tuned on SST-2.
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  This model reaches an accuracy of 71% on the dev set.
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  In this dataset, given a tweet, the goal was to infer the underlying topic of the tweet by choosing from four topics classes:
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+ - 0 : negatif
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+ - 1 : neutre
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+ - 2 : positif
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+
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+
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+ # Pipelining the Model
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline