PostgresML VS Hugging Face

Some excellent tools were created to represent these tasks "naturally" in SQL and even let most of the computation happen inside the database. PostgresML is a great example. It's built above PostgreSQL and provides a set of functions that allow you to train and use machine learning models with SQL. Here's how you can train a classification model for the classic handwritten digit recognition problem:. - Source: dev.to / 5 months ago

PostgresML | You know Postgres. Now you know machine learning – PostgresML. - Source: dev.to / 5 months ago

You can swap in almost any open-source model on Huggingface. HuggingFaceH4/zephyr-7b-beta, Gryphe/MythoMax-L2-13b, teknium/OpenHermes-2.5-Mistral-7B and more.If you haven't seen us here before, we're PostgresML, an open-source MLOps platform built on Postgres. We bring ML to the database rather than the other way around. Source: 5 months ago

If you haven't seen us here before, we're PostgresML, an open-source MLOps platform built on Postgres. We bring ML to the database rather than the other way around. We're incredibly passionate about keeping AI truly open. So we needed a way for our customers to easily escape OpenAI's clutches. Give it a go and let us know if we're missing any models, or what else would help you switch. Source: 5 months ago

PostgresML. Just released a drop in replacement for OpenAI’s chat completion endpoint that lets you use any open-source model you want. Source: 6 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 / 29 days ago

The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / about 1 month 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 2 months ago