Update README.md

README.md

@@ -7,14 +7,14 @@ license: apache-2.0
 <!-- Provide a quick summary of what the model is/does. -->
 
 
-**slim-sentiment-tool** is a 4_K_M quantized GGUF version of slim-sentiment, providing a small, fast inference implementation, optimized for multi-model concurrent deployment.  
+**slim-sql-tool** is a 4_K_M quantized GGUF version of slim-sentiment, providing a small, fast inference implementation, optimized for multi-model concurrent deployment.  
 
-[**slim-sentiment**](https://huggingface.co/llmware/slim-sentiment) 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-sql**](https://huggingface.co/llmware/slim-sql-1b-v0) 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-sentiment-tool", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False)  
+    snapshot_download("llmware/slim-sql-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:
@@ -22,11 +22,11 @@ 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-sentiment-tool")
+    model = ModelCatalog().load_model("slim-sql-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-sentiment-tool", verbose=True)  
+    ModelCatalog().tool_test_run("slim-sql-tool", verbose=True)  
 
 
 Slim models can also be loaded even more simply as part of a multi-model, multi-step LLMfx calls:
@@ -34,11 +34,11 @@ Slim models can also be loaded even more simply as part of a multi-model, multi-
     from llmware.agents import LLMfx
 
     llm_fx = LLMfx()
-    llm_fx.load_tool("sentiment")
-    response = llm_fx.sentiment(text)  
+    llm_fx.load_tool("sql")
+    response = llm_fx.sql(query, table_schema)  
 
 
-Note: please review [**config.json**](https://huggingface.co/llmware/slim-sentiment-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-sql-tool/blob/main/config.json) in the repository for prompt wrapping information, details on the model, and full test set.  
 
 
 ## Model Card Contact