Update README.md

README.md

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-license: apache-2.0
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 # Model Card for cerebras/Cerebras-LLaVA-7B
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 The checkpoints consists of Language encoder and projector weights of multimodal LLaVA-7B model trained with our Cerebras implementation and training recipe. 
 The vision encoder checkpoints for this model can be found at [cerebras/Cerebras-ViT-L-336-patch14-llava7b-ShareGPT4V](https://huggingface.co/cerebras/Cerebras-ViT-L-336-patch14-llava7b-ShareGPT4V)
 
@@ -11,7 +10,7 @@ The vision encoder checkpoints for this model can be found at [cerebras/Cerebras
 For full details of this model and training details, please read our upcoming blog post.
 
 ## License
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+Cerebras-Llava is licensed under the LLAMA 2 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved.
 
 ## Model Architecture
 Cerebras-LLaVA-7B is a transformer model with the following architecture details
@@ -20,7 +19,6 @@ Cerebras-LLaVA-7B is a transformer model with the following architecture details
 * Projector: the projector module that connects the LLM and Vision encoder part consists of two linear layers with gelu activation (mlp2x-gelu)
 
 ## Loading the model
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 This model can directly be loaded using the [LLaVa source code repository](https://github.com/haotian-liu/LLaVA). For installation, please refer to the [instructions in source code repository](https://github.com/haotian-liu/LLaVA?tab=readme-ov-file#install).
 We perform all our evaluations using the LLaVA source code repository scripts.
 
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 ```
 
 ## Intended Use
-Primary intended uses: The primary use of LLaVA is research on large multimodal models and chatbots.
-
-Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence
+_Primary intended uses_: The primary use of LLaVA is research on large multimodal models and chatbots.
 
+_Primary intended users_: The primary intended users of the model are researchers(both academic and industry) in computer vision, natural language processing, machine learning, and artificial intelligence
 
+## Limitations and Bias
+The pre-training dataset may have contained offensive or inappropriate content, even after applying data cleansing filters, which can be reflected in the model-generated text. 
+We recommend that users exercise caution when using these models for their applications or any use case that may cause deliberate or unintentional harm to others. This model is for demonstration purpose only.
 ## Acknowledgements
-We are thankful to all Cerebras engineers that made this work possible.
-
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+We are thankful to all Cerebras engineers that made this work possible.