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intended use update

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  1. README.md +2 -3
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  value: 19.46
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  veriefied: false
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  ---
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- > IMPORTANT: This model card is an early draft, the final version will available in Hugging Face on Oct 21st, 2024
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  <!-- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/62cd5057674cdb524450093d/1hzxoPwqkBJXshKVVe6_9.png) -->
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- ![image/png](granite-3_0-language-models_Group_1.png)
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  # Granite-3.0-2B-Base
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  ## Usage
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  ### Intended use
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- Prominent use cases of LLMs in text-to-text generation include summarization, text classification, extraction, question-answering, and more. All Granite Base models are able to handle these tasks as they were trained on a large amount of data from various domains. Moreover, all Granite language model can serve as baseline to create specialized models for specific application scenarios.
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  ### Generation
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  This is a simple example of how to use **Granite-3.0-2B-Base** model.
 
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  value: 19.46
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  veriefied: false
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  ---
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  <!-- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/62cd5057674cdb524450093d/1hzxoPwqkBJXshKVVe6_9.png) -->
 
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  # Granite-3.0-2B-Base
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  ## Usage
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  ### Intended use
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+ Prominent use cases of LLMs in text-to-text generation include summarization, text classification, extraction, question-answering, and more. All Granite Base models are able to handle these tasks as they were trained on a large amount of data from various domains. Moreover, they can serve as baseline to create specialized models for specific application scenarios.
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  ### Generation
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  This is a simple example of how to use **Granite-3.0-2B-Base** model.