Now that I’ve integrated Microsoft Word locally with several local LLM servers, it’s time to put its capabilities to the test. I’ll be benchmarking Microsoft Copilot in Word […]
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Use KoboldCpp in Microsoft Word Locally. No Recurring Inference Costs.
Looking for a Microsoft Copilot alternative without recurring inference costs? You might consider utilizing KoboldCpp in combination with LLMs directly within Microsoft Word. KoboldCpp is an easy-to-use AI […] read more
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Use Ollama in Microsoft Word Locally. No Recurring Inference Costs.
If you’re seeking an alternative to Microsoft Copilot that avoids recurring inference costs, consider using Ollama alongside local LLMs directly within Microsoft Word. Ollama is an open-source initiative […] read more
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Use LocalAI in Microsoft Word Locally. No Recurring Inference Costs.
Looking for a Microsoft Copilot alternative without recurring inference costs? Consider using LocalAI with local LLMs directly within Microsoft Word. LocalAI is a free, open-source alternative to OpenAI […] read more
Tutorial
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A local alternative to Microsoft Copilot in Word
Large language models (LLMs) have been rapidly advancing over the past few years. While bigger and more powerful versions are being developed in the cloud, there’s a growing […]
Demo 1: Using AnythingLLM in Microsoft Word
Demo 2: Using LM Studio in Microsoft Word (local model: Llama 3.2)
Demo 3: Using Transformer Lab in Microsoft Word (local model: Phi-4)
Demo 4: Using Ollama in Microsoft Word (local model: Llama 3.2)
Demo 5: Using llama.cpp in Microsoft Word (local model: gemma-2b)
Demo 6: Using LocalAI in Microsoft Word (local model: Llama 3.2)
Demo 7: Using KoboldCpp in Microsoft Word (local model: mistral 2.2)
Demo 8: Using Xinference in Microsoft Word (local model: Llama 2)
Demo 9: Using OpenLLM in Microsoft Word (local model: llama3.2:1b)
Demo 10: Using LiteLLM in Microsoft Word (gemini-1.5-flash, if cloud-based model is preferred)
Demo 11: Empowering Your Team with Phi-4 in Microsoft Word within Your Intranet