Update README.md with new model card content

README.md

@@ -6,7 +6,7 @@ tags:
 - keras
 pipeline_tag: text-generation
 ---
-## Model Overview
+### Model Overview
 BLOOM as described in as descriped in [BLOOM: A 176B-Parameter Open-Access Multilingual Language Model](https://arxiv.org/pdf/2211.05100.pdf), is a large language model published by BigScience. BLOOM is able to output coherent text in 46 languages and 13 programming languages. BLOOM models range in size from 0.5 billion to 3 billion parameters. See the model card below for benchmarks, data sources, and intended use cases.
 
 Weights are released under the [RAIL License](https://www.licenses.ai/ai-licenses). Keras model code is released under the [Apache 2 License](https://github.com/keras-team/keras-hub/blob/master/LICENSE).
@@ -47,4 +47,5 @@ The following model checkpoints are provided by the Keras team. Full code exampl
 
 ## Prompts
 
-The performance may vary depending on the prompt. For BLOOMZ models, we recommend making it very clear when the input stops to avoid the model trying to continue it. For example, the prompt "Translate to English: Je t'aime" without the full stop (.) at the end, may result in the model trying to continue the French sentence. Better prompts are e.g. "Translate to English: Je t'aime.", "Translate to English: Je t'aime. Translation:" "What is "Je t'aime." in English?", where it is clear for the model when it should answer. Further, we recommend providing the model as much context as possible. For example, if you want it to answer in Telugu, then tell the model, e.g. "Explain in a sentence in Telugu what is backpropagation in neural networks.".
+The performance may vary depending on the prompt. For BLOOMZ models, we recommend making it very clear when the input stops to avoid the model trying to continue it. For example, the prompt "Translate to English: Je t'aime" without the full stop (.) at the end, may result in the model trying to continue the French sentence. Better prompts are e.g. "Translate to English: Je t'aime.", "Translate to English: Je t'aime. Translation:" "What is "Je t'aime." in English?", where it is clear for the model when it should answer. Further, we recommend providing the model as much context as possible. For example, if you want it to answer in Telugu, then tell the model, e.g. "Explain in a sentence in Telugu what is backpropagation in neural networks.".
+