While looking into how to create text embeddings quickly and directly, we discovered a few helpful tools that allowed us to achieve our goal. Consequently, we created an easy-to-use PHP extension that can generate text embeddings. This extension lets you pick any model from Sentence Transformers on HuggingFace. It is built on the CandleML framework, which is written in Rust and is a part of the well-known... - Source: dev.to / about 17 hours ago
These libraries are fundamental for building and training our GPT model. PyTorch is a deep learning framework that provides flexibility and speed, while the Transformers library by Hugging Face offers pre-trained models and tokenizers, including GPT-2. - Source: dev.to / 5 days ago
Hugging Face is a company and community platform making AI accessible through open-source tools, libraries, and models. It is most notable for its transformers Python library, built for natural language processing applications. This library provides developers a way to integrate ML models hosted on Hugging Face into their projects and build comprehensive ML pipelines. - Source: dev.to / 13 days ago
We will use the OpenAI embeddings API to convert the content of the blog posts into vector embeddings. You will need to sign up for an API key on the OpenAI website to use the API. You will need to provide your credit card information as there is a cost associated with using the API. You can review the pricing on the OpenAI website. There are alternatives to generate embeddings. Hugging Face provides... - Source: dev.to / 12 days ago
Hugging-face 🤗 is a repository to host all the LLM models available in the world. https://huggingface.co/. - Source: dev.to / 20 days 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 / about 2 months ago
The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / about 2 months 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 / 2 months 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 / 2 months ago
New models can be added by downloading GGUF format models to the models sub-directory from https://huggingface.co/. - Source: dev.to / 2 months ago
I've been trying to keep up with the advances in the world of AI and LLMs. NLP was a world that I knew pretty well 7 years ago, when I knew most of the major NLP libraries, and their various strengths and weaknesses. However, nowadays, I'm having trouble finding good discussions about the real uses of the LLMs. I have gone to Hugging Face, and the amount of data there is overwhelming, but it seems poorly... - Source: Hacker News / 3 months ago
We are going to use all-MiniLM-L6-v2 model from hugging face. - Source: dev.to / 3 months ago
Log in to Hugging Face. You can create an account for free if you don't have one. - Source: dev.to / 4 months ago
Huggingface.co - Build, train, and deploy NLP models for Pytorch, TensorFlow, and JAX. Free up to 30k input characters/mo. - Source: dev.to / 4 months ago
I used huggingface for this challenge. You can find the documentation here. - Source: dev.to / 6 months ago
Hugging Face is a multifaceted platform that plays a crucial role in the landscape of artificial intelligence, particularly in the field of natural language processing (NLP) and generative AI. It encompasses various elements that work together to empower users to explore, build, and share AI applications. - Source: dev.to / 6 months ago
It is a generic bot, probably one of the smaller Llama models from Facebook that was told to be an ahole. There is nothing to it. You can have your own. Just go to https://huggingface.co/. Source: 6 months ago
I wanted to put together a little LLM experiment for a club hackathon and I ended up attempting to implement a local GPT. I came across this site which seems to be a resource for researchers to try out different trained models: https://huggingface.co/. Source: 6 months ago
If you weren’t already aware of this, there is a whole website that has a variety of AI models that you can self host. Source: 6 months ago
The /r/LocalLLaMA subreddit is all about them, and Huggingface hosts hundreds of thousands of models of every variety - over 35,000 large language models in the vein of ChatGPT. Source: 6 months ago
Go to the official Hugging Face website at https://huggingface.co/ and signup or signin accordingly. - Source: dev.to / 6 months ago
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Great resource and community for machine learning and AI.
Excellent platform for AI developers.