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Hello everyone, new to LLMs. I am working on my thesis project. The whole idea is to create a mixed reality voice assistant that can control some devices in a room and you can have with it a more intelligent conversation compared to other voice assistants(Alexa,Google, etc.). I thought initially to use wit.ai for the extraction of commands and if it's not a recognized command to send a request to a chatgpt API.... Source: 5 months ago
I can't find anything wrong with the code you posted. It is possible that wit.ai is expecting some default header that Unity is not sending (and that you are not setting). Source: about 1 year ago
Even though this was made for VR hopefully the scripts for wit.ai and GPT will be helpful to anyone who wants to explore this topic and doesn't know where to start. Source: about 1 year ago
Hey HN, We're Alex, Martin and Laurent. We previously founded [Wit.ai](http://wit.ai/) (W14), which we sold to Facebook in 2015. Since 2019, we've been working on Nabla (https://www.nabla.com), an intelligent assistant for health practitioners. When GPT-3 was released in 2020, we investigated it's usage in a medical context[0], to mixed results. Since then we’ve kept exploring opportunities at the intersection of... - Source: Hacker News / about 1 year ago
Thank you, that's helpful except that currently we're not running our own server. I'm currently using wit.ai for NLP which is a web API service provided by Meta. I'm trying to budget for what it would cost to roll out our own on a private cloud. 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 / 12 days ago
The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / 18 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 / 24 days 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 / 24 days 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
Dialogflow - Conversational UX Platform. (ex API.ai)
Replika - Your Ai friend
Botpress - Open-source platform for developers to build high-quality digital assistants
LangChain - Framework for building applications with LLMs through composability
Microsoft Bot Framework - Framework to build and connect intelligent bots.
Mitsuku - Browser-based, AI chat bot.