updated model card

README.md

@@ -72,9 +72,13 @@ print(tokenizer.decode(outputs[0]))
 
 The pretraining dataset of the model was filtered for permissive licenses only. Nevertheless, the model can generate source code verbatim from the dataset. The code's license might require attribution and/or other specific requirements that must be respected. We provide a [search index](https://huggingface.co/spaces/bigcode/starcoder-search) that let's you search through the pretraining data to identify where generated code came from and apply the proper attribution to your code.
 
+# Benefits
+
+Large code models require specialized hardware like GPUs for inference, highlighting the need for research into building small code models that can be deployed on developer desktops.  This model addresses the gap by focusing on the development of a small Java code model and introducing a quantized version (in different forms like GGML, GGUF) of NT-Java-1.1B, which performs comparably to open 1.1B models on MultiPL-E Java code benchmarks, making it ideal for desktop deployment.
+
 # Limitations
 
-The model has been trained on source code from 80+ programming languages. The predominant natural language in source code is English although other languages are also present. As such the model is capable of generating code snippets provided some context but the generated code is not guaranteed to work as intended. It can be inefficient, contain bugs or exploits. See [the paper](https://drive.google.com/file/d/1cN-b9GnWtHzQRoE7M7gAEyivY0kl4BYs/view) for an in-depth discussion of the model 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.
 
 # Training