Update README.md

README.md

@@ -8,9 +8,9 @@ license: other
 
 **dragon-yi-answer-tool** is a quantized version of DRAGON Yi 6B, with 4_K_M GGUF quantization, providing a fast, small inference implementation for use on CPUs.  
 
-[**DRAGON Yi 6B**](https://huggingface.co/llmware/dragon-yi-6b-v0) is a fact-based question-answering model, optimized for complex business documents.  
+[**dragon-yi-6b**](https://huggingface.co/llmware/dragon-yi-6b-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-yi-answer-tool", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False)  
@@ -19,8 +19,8 @@ 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-yi-answer-tool")            
-    response = model.inference(query, text_sample)  
+    model = ModelCatalog().load_model("dragon-yi-answer-tool")            
+    response = model.inference(query, add_context=text_sample)  
 
 Note: please review [**config.json**](https://huggingface.co/llmware/dragon-yi-answer-tool/blob/main/config.json) in the repository for prompt wrapping information, details on the model, and full test set.