Update README.md

README.md

@@ -8,9 +8,9 @@ license: apache-2.0
 
 **dragon-mistral-answer-tool** is a quantized version of DRAGON Mistral 7B, with 4_K_M GGUF quantization, providing a fast, small inference implementation for use on CPUs.  
 
-[**DRAGON Mistral 7B**](https://huggingface.co/llmware/dragon-mistral-7b-v0) is a fact-based question-answering model, optimized for complex business documents.  
+[**dragon-mistral-7b**](https://huggingface.co/llmware/dragon-mistral-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:  
+To pull the model via API:  
 
     from huggingface_hub import snapshot_download           
     snapshot_download("llmware/dragon-mistral-answer-tool", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False)  
@@ -19,7 +19,7 @@ We are providing as a separate repository that can be pulled directly:
 Load in your favorite GGUF inference engine, or try with llmware as follows:
 
     from llmware.models import ModelCatalog  
-    model = ModelCatalog().load_model("llmware/dragon-mistral-answer-tool")            
+    model = ModelCatalog().load_model("dragon-mistral-answer-tool")            
     response = model.inference(query, text_sample)  
 
 Note: please review [**config.json**](https://huggingface.co/llmware/dragon-mistral-answer-tool/blob/main/config.json) in the repository for prompt wrapping information, details on the model, and full test set.