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I run one. I built an iMessage-like frontend to it using plain JS and a Python websocket backend. I mostly just use it for curiosity and playing with different prompts. I only have 16GB of RAM to dedicate to it, so I use an 8B parameter model which is enough for fun and chitchat, but I don't find it good enough to replace ChatGPT. https://github.com/nomic-ai/gpt4all. - Source: Hacker News / 8 months ago
You can run the likes of GPT4All now, you can even use it to query local factual documents and source material, rather than make stuff up: https://github.com/nomic-ai/gpt4all. Source: 8 months ago
Agreed. Gpt4all[1] offers a similar 'simple setup' but with application exe downloads, but is arguably more like open core because the gpt4all makers (nomic?) want to sell you the vector database addon stuff on top. [1]https://github.com/nomic-ai/gpt4all I like this one because it feels more private / is not being pushed by a company that can do a rug pull. This... - Source: Hacker News / 9 months ago
For what it's worth, I haven't tried them yet, but there are also open-source large-language models and text-to-speech models. Source: 10 months ago
Neat! I've been working on Khoj, which does something analogous. Khoj works best with natural language documents, so it's good with documentation (i.e., READMEs), not so much with code. First I've heard of GPT4All; this is super awesome. Source: 10 months 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 / 19 days ago
The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / 25 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
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