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 AnythingLLM in Microsoft Word Locally. No Recurring Inference Costs.
Looking for a Microsoft Copilot alternative without recurring inference costs? Consider using AnythingLLM with local LLMs directly within Microsoft Word. AnythingLLM aims to be the easiest to use, […] read more
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Use Phi-4 in Microsoft Word Locally. No Inference Fee Required.
Looking for a Microsoft Copilot alternative without recurring inference costs? Consider using local LLMs directly within Microsoft Word. For example, Mehul’s post highlights that Phi-4 is currently considered […] read more
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Tailor LLM’s responses to your personal style in Microsoft Word
This morning, I discovered that Anthropic has introduced a new feature for writing in personal styles. To learn more about this feature, I visited their announcement page and […] 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