Update README.md

README.md

@@ -6,23 +6,20 @@ license: llama2
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-**dragon-llama-qa-tool** is a quantized version of DRAGON Llama 7B, with 4_K_M GGUF quantization, providing a fast, small inference implementation for use on CPUs.  
+**dragon-llama-answer-tool** is a quantized version of DRAGON Llama 7B, with 4_K_M GGUF quantization, providing a fast, small inference implementation for use on CPUs.  
 
 [DRAGON LLama 7B](https://huggingface.co/llmware/dragon-llama-7b-v0) is a fact-based question-answering model, optimized for complex business documents.  
 
 We are providing as a separate repository that can be pulled directly:  
 
-    from huggingface_hub import snapshot_download  
-
+    from huggingface_hub import snapshot_download           
     snapshot_download("llmware/dragon-llama-answer-tool", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False)  
     
 
 Load in your favorite GGUF inference engine, or try with llmware as follows:
 
-    from llmware.models import ModelCatalog
-
-    model = ModelCatalog().load_model("llmware/dragon-llama-qa-tool")            
-    
+    from llmware.models import ModelCatalog  
+    model = ModelCatalog().load_model("llmware/dragon-llama-answer-tool")            
     response = model.inference(query, text_sample)  
 
 Note: please review the config.json file in the repository for prompt wrapping information, details on the model, and full test set.