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Update README.md

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@@ -3,7 +3,7 @@ license: apache-2.0
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  inference: false
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  ---
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- # Model Card for Model ID
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  <!-- Provide a quick summary of what the model is/does. -->
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@@ -14,7 +14,7 @@ slim-nli has been fine-tuned for **natural language inference (nli)** function c
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  &nbsp;&nbsp;&nbsp;&nbsp;`{"evidence": ["contradicts"]}`
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- SLIM models are designed to provide a flexible natural language generative model that can be used as part of a multi-step, multi-model LLM-based automation workflow.
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  Each slim model has a 'quantized tool' version, e.g., [**'slim-nli-tool'**](https://huggingface.co/llmware/slim-nli-tool).
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@@ -81,6 +81,12 @@ Each slim model has a 'quantized tool' version, e.g., [**'slim-nli-tool'**](htt
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  from llmware.models import ModelCatalog
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  slim_model = ModelCatalog().load_model("llmware/slim-nli")
 
 
 
 
 
 
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  response = slim_model.function_call(text,params=["evidence"], function="classify")
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  print("llmware - llm_response: ", response)
 
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  inference: false
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  ---
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+ # SLIM-NLI
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  <!-- Provide a quick summary of what the model is/does. -->
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  &nbsp;&nbsp;&nbsp;&nbsp;`{"evidence": ["contradicts"]}`
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+ SLIM models are designed to generate structured outputs that can be used programmatically as part of a multi-step, multi-model LLM-based automation workflow.
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  Each slim model has a 'quantized tool' version, e.g., [**'slim-nli-tool'**](https://huggingface.co/llmware/slim-nli-tool).
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  from llmware.models import ModelCatalog
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  slim_model = ModelCatalog().load_model("llmware/slim-nli")
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+
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+ # input text - expects two statements - the first is evidence, and the second is a conclusion
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+ text1 = "The stock market declined yesterday as investors worried increasingly about the slowing economy."
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+ text2 = "Investors are positive about the market."
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+ text = "Evidence: " + text1 + "\n" + "Conclusion: " + text2
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+
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  response = slim_model.function_call(text,params=["evidence"], function="classify")
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  print("llmware - llm_response: ", response)