Update README.md

README.md

@@ -10,7 +10,9 @@ license: apache-2.0
 
 slim-sentiment has been fine-tuned for **sentiment analysis** function calls, generating output consisting of JSON dictionary corresponding to specified keys.  
 
-Each slim model has a corresponding 'tool' in a separate repository, e.g., [**'slim-sentiment-tool'**](https://huggingface.co/llmware/slim-sentiment-tool), which a 4-bit quantized gguf version of the model that is intended to be used for inference.  
+Each slim model has a corresponding 'tool' in a separate repository, e.g.,  
+
+[**'slim-sentiment-tool'**](https://huggingface.co/llmware/slim-sentiment-tool), which a 4-bit quantized gguf version of the model that is intended to be used for inference.  
 
 Inference speed and loading time is much faster with the 'tool' versions of the model.   
 
@@ -42,7 +44,7 @@ All of the SLIM models use a novel prompt instruction structured as follows:
 
     "<human> " + text + "<classify> " + keys + "</classify>" + "/n<bot>: "
 
-=
+
 ## How to Get Started with the Model
 
 The fastest way to get started with BLING is through direct import in transformers:
@@ -87,7 +89,6 @@ The fastest way to get started with BLING is through direct import in transforme
     except:
         print("could not convert to json automatically - ", output_only)
 
-   '''
    
 ## Using as Function Call in LLMWare