Update README.md

README.md

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 pipeline_tag: zero-shot-classification
 ---
 
+## Presentation
+We introduce the Bloomz-560m-NLI model, fine-tuned on the [Bloomz-560m-chat-dpo](https://huggingface.co/cmarkea/bloomz-560m-dpo-chat) foundation model. This model is trained on a Natural Language Inference (NLI) task in a language-agnostic manner. The NLI task involves determining the semantic relationship between a hypothesis and a set of premises, often expressed as pairs of sentences. It should be noted that hypotheses and premises are randomly chosen between English and French, with each language combination representing a probability of 25%.
+
+## Zero-shot Classification
+The primary appeal of training such models lies in their zero-shot classification performance. This means the model is capable of classifying any text with any label without specific training. What sets the Bloomz-560m-NLI LLMs apart in this realm is their ability to model and extract information from significantly more complex and lengthy test structures compared to models like BERT, RoBERTa, or CamemBERT.
+
 ```python
 from transformers import pipeline