I’m doing research on AI-solutions that enable automatic translation, transcription and dubbing of Youtube videos, and need your help. So far I’ve found 4 tools that seem to match my requirements in terms of usability and translation accuracy. Does anyone have experiences to share about using some of these, or similar tools? How accurate are these kind of tools in general, are they worth spending money... Source: about 1 year ago

I wanted to get a project for running my own pipeline with somewhat interchangeable parts. Models can be swapped around so that you can make the most of the latest models either available on Hugginface, OpenAI or wherever. - Source: dev.to / about 1 month ago

Log in to your Huggingface account at https://huggingface.co. Click Access Token in the menu to generate a new token. - Source: dev.to / 11 days ago

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 / 17 days 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 / 21 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 / 29 days ago