Upload README.md

README.md

@@ -6,27 +6,23 @@ license: apache-2.0
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-**bling-qa-tool** is a 4_K_M quantized GGUF version of bling-tiny-llama-1b-v0, providing a small, fast inference implementation.
+**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.  
 
-Load in your favorite GGUF inference engine (see details in config.json to set up the prompt template), or try with llmware as follows:
+[**dragon-mistral-7b**](https://huggingface.co/llmware/dragon-mistral-7b-v0) is a fact-based question-answering model, optimized for complex business documents.  
 
-    from llmware.models import ModelCatalog
+To pull the model via API:  
 
-    # to load the model and make a basic inference
-    qa_tool = ModelCatalog().load_model("bling-qa-tool")
-    response = qa_tool.function_call(text_sample)  
-
-    # this one line will download the model and run a series of tests
-    ModelCatalog().test_run("bling-qa-tool", verbose=True)  
-    
+    from huggingface_hub import snapshot_download           
+    snapshot_download("llmware/dragon-mistral-answer-tool", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False)  
     
-Slim models can also be loaded even more simply as part of a multi-model, multi-step LLMfx calls:
 
-    from llmware.agents import LLMfx
+Load in your favorite GGUF inference engine, or try with llmware as follows:
+
+    from llmware.models import ModelCatalog  
+    model = ModelCatalog().load_model("dragon-mistral-answer-tool")            
+    response = model.inference(query, add_context=text_sample)  
 
-    llm_fx = LLMfx()
-    llm_fx.load_tool("quick_question")
-    response = llm_fx.quick_question(text)
+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.  
 
 
 ### Model Description
@@ -37,17 +33,9 @@ Slim models can also be loaded even more simply as part of a multi-model, multi-
 - **Model type:** GGUF 
 - **Language(s) (NLP):** English
 - **License:** Apache 2.0
-- **Quantized from model:** llmware/bling-tiny-llama-1b-v0 
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-Model instructions, details and test samples have been packaged into the config.json file in the repository, along with the GGUF file.   
-
+- **Quantized from model:** [llmware/dragon-mistral](https://huggingface.co/llmware/dragon-mistral-7b-v0/)
+  
 
 ## Model Card Contact
 
-Darren Oberst & llmware team
-
-
+Darren Oberst & llmware team