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bloomz-7b1-mt-nli

Zero-Shot Classification

text-classification

text-generation-inference

Inference Endpoints

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Cyrile commited on Mar 22

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@@ -56,7 +56,7 @@ And now the hypothesis in French and the premise in English (cross-language cont
 # Zero-shot Classification
 The primary interest of training such models lies in their zero-shot classification performance. This means that the model is able to classify any text with any label
-without a specific training. What sets the Bloomz-3b-NLI LLMs apart in this domain is their ability to model and extract information from significantly more complex
 and lengthy text structures compared to models like BERT, RoBERTa, or CamemBERT.
 The zero-shot classification task can be summarized by:

 # Zero-shot Classification
 The primary interest of training such models lies in their zero-shot classification performance. This means that the model is able to classify any text with any label
+without a specific training. What sets the Bloomz-7b1-mt-NLI LLMs apart in this domain is their ability to model and extract information from significantly more complex
 and lengthy text structures compared to models like BERT, RoBERTa, or CamemBERT.
 The zero-shot classification task can be summarized by: