voorhs

voorhs's Stars

• Darinochka/AutoIntent-experiments

  Language:Jupyter Notebook1

• MasterGroosha/aiogram-3-guide

  Пишем Telegram-ботов с aiogram 3.x

  Language:Python942132

• VELIKII-DIVAN/FlexiPrompt

  Language:Python3

• substratusai/stapi

  Sentence Transformers API: An OpenAI compatible embedding API server

  Language:HTML377

• srush/GPU-Puzzles

  Solve puzzles. Learn CUDA.

  Language:Jupyter Notebook10k863

• GoogleChrome/chrome-extensions-samples

  Chrome Extensions Samples

  Language:JavaScript15.7k8.3k

• deeppavlov/dialog_flow_demo

  Language:Python32

• deeppavlov/chatsky

  Chatsky is a free and open-source software stack for creating chatbots, released under the terms of Apache License 2.0.

  Language:Python329

• deeppavlov/chatsky-llm-autoconfig

  Language:Jupyter Notebook51

• bigscience-workshop/petals

  🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading

  Language:Python9.3k525

• vafakaramzadegan/Docker-NGINX-SSL-FastAPI

  FastAPI, NGINX, Docker: An API boilerplate with self-signed SSL in Docker.

  Language:Dockerfile2

• davidadamojr/TextRank

  Python implementation of TextRank algorithm for automatic keyword extraction and summarization using Levenshtein distance as relation between text units. This project is based on the paper "TextRank: Bringing Order into Text" by Rada Mihalcea and Paul Tarau. https://web.eecs.umich.edu/~mihalcea/papers/mihalcea.emnlp04.pdf

  Language:Python767225

• zhanymkanov/fastapi-best-practices

  FastAPI Best Practices and Conventions we used at our startup

  9.6k709

• DJWOMS/FastAPI_ru

  В этом репозитории находится полезная информация, собранная участниками русского сообщества FastAPI.

  22011

• mryab/efficient-dl-systems

  Efficient Deep Learning Systems course materials (HSE, YSDA)

  Language:Jupyter Notebook702112

• techkuz/fast-api-rag-clickhouse-yc

  Language:Jupyter Notebook161

• microsoft/Phi-3CookBook

  This is a Phi-3 book for getting started with Phi-3. Phi-3, a family of open sourced AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks.

  Language:Jupyter Notebook2.6k275

• pavviaz/itmo_convai_course

  This repository is created for ITMO-MIPT Conversational NLP course

  Language:Python21

• alpotekhin/neuroscholar

  Language:Python1

• Tanchik24/DFFSearch_BOT

  Language:Python1

• CAIDevBeauty/faberlic_chat_bot

  Language:Python1

• ggerganov/llama.cpp

  LLM inference in C/C++

  Language:C++69.2k9.9k

• iver56/audiomentations

  A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.

  Language:Python1.9k193

• embeddings-benchmark/mteb

  MTEB: Massive Text Embedding Benchmark

  Language:Jupyter Notebook2k283

• FortsAndMills/RL-Theory-book

  Reinforcement learning theory book about foundations of deep RL algorithms with proofs.

  Language:TeX28920

• MaxenceGiraud/MachineLearningAlgos

  Personal reimplementation of some ML algorithms for learning purposes

  Language:Python92

• githubharald/CTCDecoder

  Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.

  Language:Python818182

• 1rgs/jsonformer

  A Bulletproof Way to Generate Structured JSON from Language Models

  Language:Jupyter Notebook4.5k158

• ymd-h/cpprb

  Fast Flexible Replay Buffer Library (Mirror repository of https://gitlab.com/ymd_h/cpprb)

  Language:Python7210

• locuslab/icnn

  Input Convex Neural Networks

  Language:Python28251