Generate Summaries with Topic Focus using CPU-friendly Model SLIM

Explore one of our most unique models for generating both general and topic-focused summaries with CPU-friendly SLIM Summary model. Great for generating python list of summaries with an experimental feature that allows you to specify the number of key points or bullet points.
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Model used (tool is the GGUF version):
huggingface.co...
huggingface.co...
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[@animatorslife9733]

This is a great introduction to Slim Summary! I found the explanation of the model and its capabilities to be very clear and concise. The demonstration was helpful in understanding how to use the model in practice.
As a suggestion for improvement, it would be interesting to see how Slim Summary performs on different types of complex business text besides financial statements and earnings releases. Perhaps you could showcase some examples with legal documents or marketing materials.

[@llmware]

Thank you so much for the kind feedback! We have had extremely positive feedback for legal use cases already with this model and we will try to showcase other use cases in the future as well.

[@kipnerter]

Great video, is this model primarily trained / focused on financial summary data? Or is the purpose to be used for generic snipppets of text? I am looking to add this model to creating summaries for documents in a knowledge graph with local models at a high frequency.

[@llmware]

Our models tend to be focused on financial, legal or business use cases generally but it should work for generic snippets of text as well. Please let us know your feedback in discord after you use it - we are always looking to improve our models so your feedback is very appreciated!