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 / 1 day 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 / 14 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 / 13 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

Isn't there only two open multimodal LLMs, LLaVA and mini-gpt4? Source: 11 months ago

So we use MiniGPT-4 for image parsing, and yep it does return a pretty detailed (albeit not always accurate) description of the photo. You can actually play around with it on Huggingface here. Source: about 1 year ago

We use MiniGPT-4 first to interpret the image and then pass the results onto GPT-4. Hopefully, once GPT-4 makes its multi-modal functionality available, we can do it all in one request. Source: about 1 year ago

But I would like to bring up that there are some multi models(llava, miniGPT-4) that are built based on censored llama based models like vicuna. I tried several multi modal models like llava, minigpt4 and blip2. Llava has very good captioning and question answering abilities and it is also much faster than the others(basically real time), though it has some hallucination issue. Source: about 1 year ago

Https://minigpt-4.github.io/ <-- free image recognition, although not powered by true GPT-4. Source: about 1 year ago