Generative Ai

Всем привет! 🕵 На связи команда исследователей Яндекс Практикума. Мы с коллегами сейчас проводим исследование в рамках которого хотим уточнить у опытных специалистов в области Computer Vision и NLP требования к джунам этих специализаций. Мы очень будем рады, если найдём время на небольшой 20 минутный звонок, где ты сможешь поделиться своим видением и мнение по текущим навыкам для джунов в твой доменной области! С нас приятный бонус за общение! 🎁 Готов откликнуться? Заполни нашу форму обратной связи и мы свяжемся с тобой!

😊 HugNLP HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. HugNLP — это новая универсальная NLP библиотека основанная на Hugging Face, для повышения удобства и эффективности работы c текстами. 🖥 Github: https://github.com/wjn1996/hugnlp ⏩ Paprer: https://arxiv.org/abs/2302.14286v1 ⭐️ Dataset: https://paperswithcode.com/dataset/clue ⏩ HF for complex text classification: https://huggingface.co/blog/classification-use-cases @ai_machinelearning_big_data

InvokeAI: A Stable Diffusion Toolkit https://github.com/invoke-ai/InvokeAI

🤗 Diffusers provides pretrained diffusion models across multiple modalities, such as vision and audio, and serves as a modular toolbox for inference and training of diffusion models. https://github.com/huggingface/diffusers/tree/main/examples/community#magic-mix

xFormers - Toolbox to Accelerate Research on Transformers xFormers is: Customizable building blocks: Independent/customizable building blocks that can be used without boilerplate code. The components are domain-agnostic and xFormers is used by researchers in vision, NLP and more. Research first: xFormers contains bleeding-edge components, that are not yet available in mainstream libraries like pytorch. Built with efficiency in mind: Because speed of iteration matters, components are as fast and memory-efficient as possible. xFormers contains its own CUDA kernels, but dispatches to other libraries when relevant. https://github.com/facebookresearch/xformers

Prompt Engineering Guide https://github.com/dair-ai/Prompt-Engineering-Guide

Open source implementation for LLaMA-based ChatGPT training process. Faster and cheaper training than ChatGPT (wip) https://github.com/nebuly-ai/nebullvm/tree/main/apps/accelerate/chatllama

​​LLaMA: Open and Efficient Foundation Language Models LLaMA is a set of large language models, ranging from 7B to 65B parameters, that have been trained on publicly available datasets containing trillions of tokens. The LLaMA-13B model performs better than GPT-3 (175B) on most benchmarks, and the LLaMA-65B model is competitive with other state-of-the-art models, such as Chinchilla70B and PaLM-540B. This suggests that it is possible to achieve excellent performance in language modeling without relying on proprietary or inaccessible datasets. Paper: https://research.facebook.com/publications/llama-open-and-efficient-foundation-language-models/ Code: https://github.com/facebookresearch/llama A detailed unofficial overview of the paper: https://andlukyane.com/blog/paper-review-llama #deeplearning #nlp #transformer #sota #languagemodel

📡 Learning Visual Representations via Language-Guided Sampling New approach deviates from image-text contrastive learning by relying on pre-trained language models to guide the learning rather than minimize a cross-modal similarity. Новый альтернативный подход к визуальному обучению: с использованием языкового сходства для выборки семантически схожих пар изображений. 🖥 Github: https://github.com/mbanani/lgssl ⭐️Paper: https://arxiv.org/abs/2302.12248v1 ⏩Pre-trained Checkpoints: https://www.dropbox.com/sh/me6nyiewlux1yh8/AAAPrD2G0_q_ZwExsVOS_jHQa?dl=0 💻 Dataset : https://paperswithcode.com/dataset/redcaps ai_machinelearning_big_data

Vector search demo with the arXiv paper dataset, HuggingFace, OpenAI, FastAPI, React, and Redis as the vector database. https://github.com/RedisVentures/redis-arXiv-search https://docsearch.redisventures.com/

Появился сервис AIcyclopedia, в котором собрано более 1000 ИИ-инструментов по категориям из сотен источников, более 900 промтов и инструкций ChatGPT, подкасты и даже фильмы. Всё это по нейросетям в одном месте, чтобы было намного проще найти то, что вас интересует. Ссылка r/#InternetIsBeautiful

🔍 Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-3 and alike). Haystack offers production-ready tools to quickly build ChatGPT-like question answering, semantic search, text generation, and more. https://github.com/deepset-ai/haystack/

Streamline AI & ML Product Delivery https://github.com/jina-ai/jina