| name | 喘ぎ声表現 | |||||||
|---|---|---|---|---|---|---|---|---|
| description | 日本語のエロライトノベル・官能小説を中心に、喘ぎ声(あえぎごえ)の表現を多様で豊かにするためのスキル。定義・研究・ノウハウを網羅。キャラクターの理性・快感度・シチュエーションに即した自然でエロティックな喘ぎ声を、下品レベル1~4を指定することで生成可能。 | |||||||
| version | 2.0.0 | |||||||
| tags |
|
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This guide walks you through creating a high-performance Windows 11 virtual machine (VM) on Fedora Silverblue using GPU passthrough technology. This setup allows you to run Windows applications that require dedicated graphics performance while keeping your primary system secure with Fedora Silverblue.
GPU passthrough allows your virtual machine to use your dedicated graphics card directly, providing near-native gaming and graphics performance in Windows while running on Linux. This is different from typical virtualization where graphics performance is limited.
Key terms you'll encounter:
| (?i)((access_key|access_token|admin_pass|admin_user|algolia_admin_key|algolia_api_key|alias_pass|alicloud_access_key|amazon_secret_access_key|amazonaws|ansible_vault_password|aos_key|api_key|api_key_secret|api_key_sid|api_secret|api.googlemaps AIza|apidocs|apikey|apiSecret|app_debug|app_id|app_key|app_log_level|app_secret|appkey|appkeysecret|application_key|appsecret|appspot|auth_token|authorizationToken|authsecret|aws_access|aws_access_key_id|aws_bucket|aws_key|aws_secret|aws_secret_key|aws_token|AWSSecretKey|b2_app_key|bashrc password|bintray_apikey|bintray_gpg_password|bintray_key|bintraykey|bluemix_api_key|bluemix_pass|browserstack_access_key|bucket_password|bucketeer_aws_access_key_id|bucketeer_aws_secret_access_key|built_branch_deploy_key|bx_password|cache_driver|cache_s3_secret_key|cattle_access_key|cattle_secret_key|certificate_password|ci_deploy_password|client_secret|client_zpk_secret_key|clojars_password|cloud_api_key|cloud_watch_aws_access_key|cloudant_password|cloudflare_api_key|cloudflare_auth_k |
| Office 2013 Home and Student Russian https://officeredir.microsoft.com/r/rlidO15C2RMediaDownload?p1=db&p2=ru-RU&p3=HomeStudentRetail | |
| Office 2013 Home and Business https://officeredir.microsoft.com/r/rlidO15C2RMediaDownload?p1=db&p2=ru-RU&p3=HomeBusinessRetail | |
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| Word 2013 https://officeredir.microsoft.com/r/rlidO15C2RMediaDownload?p1=db&p2=ru-RU&p3=WordRetail | |
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A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| """ | |
| The most atomic way to train and run inference for a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| @karpathy | |
| """ | |
| import os # os.path.exists | |
| import math # math.log, math.exp |
| # %% | |
| import os | |
| os.environ['CUDA_VISIBLE_DEVICES'] = '0' | |
| import random | |
| random.seed(42) | |
| import torch | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| from datasets import load_dataset | |
| # %% |
| #!/bin/bash | |
| # https://www.eevblog.com/forum/thermal-imaging/infiray-and-their-p2-pro-discussion/200/ | |
| # https://superuser.com/questions/1009969/how-to-extract-a-frame-out-of-a-video-using-ffmpeg | |
| # https://stackoverflow.com/questions/37960828/webcam-streaming-from-mac-using-ffmpeg | |
| # | |
| # Selected pixel format (yuv420p) is not supported by the input device. | |
| #[avfoundation @ 0x7f961cd08b40] Supported pixel formats: | |
| #[avfoundation @ 0x7f961cd08b40] uyvy422 | |
| #[avfoundation @ 0x7f961cd08b40] yuyv422 |