Update README.md

README.md

@@ -126,11 +126,11 @@ print(tokenizer.decode(outputs[0]))
 
 # Attribution & Other Requirements
 
-The pretraining dataset for the model was curated to include only data with permissive licenses. Despite this, the model is capable of generating source code verbatim from the dataset. The licenses of such code may necessitate attribution and adherence to other specific conditions. To facilitate compliance, we provide a search index that enables users to trace the origins of generated code within the pretraining data, allowing for proper attribution and adherence to licensing requirements.
+The pretraining dataset for the model was curated to include only data with permissive licenses. Despite this, the model is capable of generating source code verbatim from the dataset. The licenses of such code may necessitate attribution and adherence to other specific conditions. To facilitate compliance, we provide a [search index](https://huggingface.co/spaces/bigcode/search) that enables users to trace the origins of generated code within the pretraining data, allowing for proper attribution and adherence to licensing requirements.
 
 # Limitations
 
-The model, NT-Java-1.1B, has been trained on publicly available datasets and comes without any safety guarantees. Due to this, like all Language Models, its outputs cannot be reliably predicted and sometimes the generated code is not guaranteed to work as intended. It can also be inefficient and may contain bugs or exploits. Therefore, it's crucial for users and developers to conduct thorough safety testing and implement filtering mechanisms tailored to their needs.
+The NT-Java-1.1B model has been trained on publicly available datasets and is offered without any safety guarantees. As with all language models, its outputs are inherently unpredictable, and the generated code may not perform as expected. Additionally, the code may be inefficient or contain bugs and security vulnerabilities. Consequently, it is imperative for users and developers to undertake extensive safety testing and to implement robust filtering mechanisms tailored to their specific needs.
 
 # Training