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Based on our record, LM Studio seems to be a lot more popular than LLMOps.Space. While we know about 29 links to LM Studio, we've tracked only 1 mention of LLMOps.Space. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
LM Studio[0] is the best "i'm new here and what is this!?" tool for dipping your toes in the water. If the model supports "vision" or "sound", that tool makes it relatively painless to take your input file + text and feed it to the model. [0]: https://lmstudio.ai/. - Source: Hacker News / 10 days ago
LM Studio - Local AI development environment. - Source: dev.to / 28 days ago
If you're running LLMs locally, you've probably used Ollama or LM Studio. They're both excellent tools, but I hit some limitations. LM Studio is primarily a desktop app that can't run truly headless, while Ollama requires SSH-ing into your server every time you want to switch models or adjust parameters. - Source: dev.to / 29 days ago
LM Studio 0.3.17 introduced Model Context Protocol (MCP) support, revolutionizing how we can extend local AI models with external capabilities. This guide walks through setting up the Docker MCP Toolkit with LM Studio, enabling your local models to access 176+ tools including web search, GitHub operations, database management, and web scraping. - Source: dev.to / about 1 month ago
The real breakthrough is that Codex also supports open-source, self-hosted models. With the --oss flag or a configured profile, you can run inference locally through providers like Ollama, LM Studio, or MLX. - Source: dev.to / about 1 month ago
MlOps is not just a hyped term,its a thing actually. I am a Mlops engineer working in a big firm setting up Mlops infrastructure pf clients.Machine learning is not only about training models and deploying them to get predictions.There are lot of problems which occurs in the models post production. As time passes,model do age as well the distribution of data on which the model is trained changes (data drift)... Source: about 2 years ago
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