Update README.md

README.md

@@ -1,25 +1,26 @@
 ---
-license: cc-by-sa-4.0
+license: apache-2.0  
+inference: false  
 ---
 
-# SLIM-EXTRACT-TOOL
+# SLIM-EXTRACT-TINY-TOOL
 
 <!-- Provide a quick summary of what the model is/does. -->
 
 
-**slim-extract-tool** is a 4_K_M quantized GGUF version of slim-extract, providing a small, fast inference implementation, optimized for multi-model concurrent deployment.  
+**slim-extract-tiny-tool** is a 4_K_M quantized GGUF version of slim-extract, providing a small, fast inference implementation, optimized for multi-model concurrent deployment.  
 
 This model has been fine-tuned to implement a general-purpose extraction function that takes a custom key as input parameter, and generates a python dictionary consisting of that custom key with the value consisting of a list of the values associated with that key in the text.   
 
 The intent of SLIMs is to forge a middle-ground between traditional encoder-based classifiers and open-ended API-based LLMs.
 
 
-[**slim-extract**](https://huggingface.co/llmware/slim-extract) is part of the SLIM ("**S**tructured **L**anguage **I**nstruction **M**odel") series, providing a set of small, specialized decoder-based LLMs, fine-tuned for function-calling.
+[**slim-extract-tiny**](https://huggingface.co/llmware/slim-extract-tiny) is part of the SLIM ("**S**tructured **L**anguage **I**nstruction **M**odel") series, providing a set of small, specialized decoder-based LLMs, fine-tuned for function-calling.
 
 To pull the model via API:  
 
     from huggingface_hub import snapshot_download           
-    snapshot_download("llmware/slim-extract-tool", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False)  
+    snapshot_download("llmware/slim-extract-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-extract-tool")
+    model = ModelCatalog().load_model("slim-extract-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-extract-tool", verbose=True)  
+    ModelCatalog().tool_test_run("slim-extract-tiny-tool", verbose=True)  
 
 
-Note: please review [**config.json**](https://huggingface.co/llmware/slim-extract-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-extract-tiny-tool/blob/main/config.json) in the repository for prompt wrapping information, details on the model, and full test set.  
 
 
 ## Model Card Contact