Update README.md

README.md

@@ -1,25 +1,26 @@
 ---
-license: cc-by-sa-4.0
+license: apache-2.0  
+inference: false
 ---
 
-# SLIM-SUMMARY-TOOL
+# SLIM-SUMMARY-TINY-TOOL
 
 <!-- Provide a quick summary of what the model is/does. -->
 
 
-**slim-summary-tool** is a 4_K_M quantized GGUF version of slim-summary, providing a small, fast inference implementation, to provide high-quality summarizations of complex business documents, on a small, specialized locally-deployable model with summary output structured as a python list of key points.  
+**slim-summary-tiny-tool** is a 4_K_M quantized GGUF version of slim-summary-tiny, providing a small, fast inference implementation, to provide high-quality summarizations of complex business documents, on a small, specialized locally-deployable model with summary output structured as a python list of key points.  
 
-The size of the self-contained GGUF model binary is 1.71 GB, which is small enough to run locally on a CPU with reasonable inference speed, and has been designed to balance high-quality with the ability to deploy on a local machine.  
+The size of the self-contained GGUF model binary is ~700 MB, which is small enough to run locally on a CPU with reasonable inference speed, and has been designed to balance high-quality with the ability to deploy on a local machine.  
 
 The model takes as input a text passage, an optional parameter with a focusing phrase or query, and an experimental optional (N) parameter, which is used to guide the model to a specific number of items return in a summary list.  
 
-Please see the usage notes at:  [**slim-summary**](https://huggingface.co/llmware/slim-summary) 
+Please see the usage notes at:  [**slim-summary-tiny**](https://huggingface.co/llmware/slim-summary-tiny) 
 
 
 To pull the model via API:  
 
     from huggingface_hub import snapshot_download           
-    snapshot_download("llmware/slim-summary-tool", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False)  
+    snapshot_download("llmware/slim-summary-tiny-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:
@@ -27,14 +28,14 @@ Load in your favorite GGUF inference engine, or try with llmware as follows:
     from llmware.models import ModelCatalog  
     
     # to load the model and make a basic inference
-    model = ModelCatalog().load_model("slim-summary-tool")
+    model = ModelCatalog().load_model("slim-summary-tiny-tool")
     response = model.function_call(text_sample)  
 
     # this one line will download the model and run a series of tests
-    ModelCatalog().tool_test_run("slim-summary-tool", verbose=True)  
+    ModelCatalog().tool_test_run("slim-summary-tiny-tool", verbose=True)  
 
 
-Note: please review [**config.json**](https://huggingface.co/llmware/slim-summary-tool/blob/main/config.json) in the repository for prompt wrapping information, details on the model, and full test set.  
+Note: please review [**config.json**](https://huggingface.co/llmware/slim-summary-tiny-tool/blob/main/config.json) in the repository for prompt wrapping information, details on the model, and full test set.  
 
 
 ## Model Card Contact