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@@ -9,11 +9,11 @@ inference: false
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  **slim-sentiment** is part of the SLIM ("Structured Language Instruction Model") model series, providing a set of small, specialized decoder-based LLMs, fine-tuned for function-calling.
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- slim-sentiment has been fine-tuned for **sentiment analysis** function calls, generating output consisting of a python dictionary corresponding to specified keys.
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-
 
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  Each slim model has a corresponding 'tool' in a separate repository, e.g., [**'slim-sentiment-tool'**](https://huggingface.co/llmware/slim-sentiment-tool), which a 4-bit quantized gguf version of the model that is intended to be used for inference.
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- Inference speed and loading time is much faster with the 'tool' versions of the model, and multiple tools can be deployed concurrently and run on a local CPU-based laptop or server.
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  ### Model Description
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@@ -74,10 +74,7 @@ The intended use of SLIM models is to re-imagine traditional 'hard-coded' classi
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  print("success - converted to python dictionary automatically")
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  except:
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  print("fail - could not convert to python dictionary automatically - ", llm_string_output)
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-
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- # sample output
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- {"sentiment": ["negative"]}
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-
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  </details>
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  **slim-sentiment** is part of the SLIM ("Structured Language Instruction Model") model series, providing a set of small, specialized decoder-based LLMs, fine-tuned for function-calling.
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+ slim-sentiment has been fine-tuned for **sentiment analysis** function calls, generating output consisting of a python dictionary corresponding to specified keys, e.g.:
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+ {"sentiment": ["positive"]}
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+
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  Each slim model has a corresponding 'tool' in a separate repository, e.g., [**'slim-sentiment-tool'**](https://huggingface.co/llmware/slim-sentiment-tool), which a 4-bit quantized gguf version of the model that is intended to be used for inference.
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  ### Model Description
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  print("success - converted to python dictionary automatically")
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  except:
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  print("fail - could not convert to python dictionary automatically - ", llm_string_output)
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+
 
 
 
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  </details>
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