Focusmate VS Hugging Face

I struggle with similar feelings. For desk/at home work, the Focusmate app (focusmate.com) has been a huge help. It kind of single-handedly helped me earn back trust in myself. You get 1:1 virtual coworking sessions with another user where you follow a friendly entry/exit protocol, tell each other what your plans are and how it went at the end, and keep your camera on the whole time while you work (usually muted).... Source: 10 months ago

Maybe you can get your company to create a Focusmate group or a discord channel? If you haven’t heard of Focusmate you should definitely check it out. I wfh and absolutely could not do so without it. It gives me a fix for interaction but not too much to get me distracted and it also helps remind me to take breaks. Source: 12 months ago

Hey, I'm not sure if you work from home / remotely but if you are trying to achieve something from home, I'll just tell you about something that has really helped me: A co-working site like focusmate.com has been a game-changer for me. For some reason my productivity / commitment shoots up when I'm working alongside someone. Hope this helps. Source: 12 months ago

I occasionally run into professors using http://focusmate.com to help get through grading. Source: 12 months ago

Ive seen something like this its focusmate. I tried it once few years ago, back then it's only a one on one session. Not sure if they support something like yours. Source: about 1 year ago

HuggingFaceEmbeddings is a function that we use for converting our documents to vector which is called embedding, you can use any embedding model from huggingface, it will load the model on your local computer and create embeddings(you can use external api/service to create embeddings), then we just pass this to context and create index and store them into folder so we can reuse them and don't need to recalculate it. - Source: dev.to / 18 days ago

The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / 24 days ago

Finally, you'll need to download a compatible language model and copy it to the ~/llama.cpp/models directory. Head over to Hugging Face and search for a GGUF-formatted model that fits within your device's available RAM. I'd recommend starting with TinyLlama-1.1B. - Source: dev.to / about 1 month ago

At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / about 1 month ago

New models can be added by downloading GGUF format models to the models sub-directory from https://huggingface.co/. - Source: dev.to / about 1 month ago