TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #14993 · Jul 24
#jupyter_notebook Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability. https://github.com/langchain-ai/rag-from-scratch
Hashtags
Search: #composer
@dooooshno · Post #921 · 03/28/2024, 02:15 PM
Пришло время! Я работаю саунд продюссером, SFX, игры, реклама и участие в создании архитектуры проекта #musicproduction#sounddesign#composer#soundegineer И конечно свожу треки, очень красиво и главное бережно к артисту и его душевной организации) Если вам или кому-то из ваших друзей/знакомых нужен такой специалист – Смело пишите , отправляйте ему это сообщение 💼Портфолио: http://leonovaportfolio.tilda.ws/page44575443.html
@djangoproject · Post #535 · 12/28/2017, 10:12 AM
https://docs.pipenv.org/ #Pipenv — the officially recommended #Python#packaging tool from Python.org, free (as in freedom). Pipenv is a tool that aims to bring the best of all packaging worlds (#bundler, #composer, #npm, #cargo, #yarn, etc.) to the Python world. #Windows is a first–class citizen, in our world. It automatically creates and manages a #virtualenv for your projects, as well as adds/removes #packages from your #Pipfile as you install/uninstall packages. It also generates the ever–important Pipfile.lock, which is used to produce deterministic builds.