#html #art #chinese #landscape #painting #perlin_noise #procedural_generation #scrollable

https://github.com/LingDong-/shan-shui-inf

#python #chinese_ocr #cnn #crnn #data_mining #deep_learning #image_processing #lstm #machine_learning #ocr #optical_character_recognition #pytorch #scene_text #scene_text_recognition

https://github.com/JaidedAI/EasyOCR

#cplusplus #board_game #chinese_chess #engine #free #pikafish #powerful #stockfish #strongest #uci #xiangqi

https://github.com/official-pikafish/Pikafish

#dockerfile #chinese #cookbook #cooking #dishes #recipes

This guide is designed for programmers who want to cook at home, especially during times of isolation. It provides clear and precise recipes tailored for those familiar with formal languages, making it easier to follow. The guide includes a wide range of dishes categorized by difficulty, type (vegetarian, meat, seafood, breakfast, staples, semi-finished products, soups, drinks, condiments, and desserts). You can also contribute to the project by submitting pull requests or adding new recipes. Additionally, there are tips on kitchen preparation and advanced cooking techniques. This resource helps you cook efficiently and enjoyably while staying at home.

https://github.com/Anduin2017/HowToCook

#python #book #chinese #computer_vision #deep_learning #machine_learning #natural_language_processing #notebook #python

This resource, "Dive into Deep Learning," is a free online book that helps you learn deep learning by doing. It provides detailed concepts, background knowledge, and executable code to help you understand the mathematical principles and implement them in practice. The book includes runnable code examples so you can see how to solve problems step-by-step and experiment with different approaches. It also allows for community feedback and continuous updates to keep up with the rapidly evolving field of deep learning. This makes it an excellent resource for anyone looking to become a deep learning practitioner, whether you're a student or an industry professional.

https://github.com/d2l-ai/d2l-zh

#xml #bibliography #bibliography_style #chinese #citation_style_language #citation_styles #csl #gbt_7714 #gbt_7714_2015

This repository provides a series of CSL (Citation Style Language) styles derived from the GB/T 7714—2015 standard, many of which support both "et al" and "等" for bilingual citations. You can download these styles from the provided links and install them in Zotero to format your references according to Chinese standards. To use, select a suitable style from the repository, set the language field for each item (e.g., `zh` for Chinese, `en` for English), and refresh your Word add-on if necessary. This helps you maintain consistent and accurate citations in your documents, especially useful for academic writing in China.

https://github.com/zotero-chinese/styles

#python #chinese #clip #computer_vision #contrastive_loss #coreml_models #deep_learning #image_text_retrieval #multi_modal #multi_modal_learning #nlp #pretrained_models #pytorch #transformers #vision_and_language_pre_training #vision_language

This project is about a Chinese version of the CLIP (Contrastive Language-Image Pretraining) model, trained on a large dataset of Chinese text and images. Here’s what you need to know This model helps you quickly perform tasks like calculating text and image features, cross-modal retrieval (finding images based on text or vice versa), and zero-shot image classification (classifying images without any labeled examples).
- **Ease of Use** The model has been tested on various datasets and shows strong performance in zero-shot image classification and cross-modal retrieval tasks.
- **Resources**: The project includes pre-trained models, training and testing codes, and detailed tutorials on how to use the model for different tasks.

Overall, this project makes it easy to work with Chinese text and images using advanced AI techniques, saving you time and effort.

https://github.com/OFA-Sys/Chinese-CLIP

#html #android #apk #c #cartoon #chinese #comics #e_hentai #ehviewer #exhentai #hentai #hentai_downloader #hentai_viwer #html5 #java #screenshot

The latest version of EhViewer, 1.9.8.7, has several important updates that benefit users. Here are the key points Many bugs have been fixed, including problems with WiFi data migration, download list sorting, and crashes related to various functions like downloading archives and displaying comments.
- **New Features** Enhanced stability and performance by optimizing download logic, adding a timeout setting for downloads, and improving the handling of historical records.
- **Security**: Updated security measures include adding user-defined network certificate permissions and fixing potential vulnerabilities.

These updates make the app more stable, efficient, and user-friendly.

https://github.com/xiaojieonly/Ehviewer_CN_SXJ

#javascript #chinese #clash #clash_chinese #shadowsocks #windows #zh_cn

This version of Clash for Windows is translated into Chinese, making it easier for Chinese users to use. It includes a simplified installation process and automatic updates. Here’s how it benefits you: you can download and install a Chinese version of Clash for Windows, which is easier to navigate if you don’t speak English. The installation program handles updates, so you don’t have to worry about manually updating the software. This makes using Clash for Windows more convenient and user-friendly for Chinese speakers.

https://github.com/Z-Siqi/Clash-for-Windows_Chinese

#python #chinese #flash_attention #large_language_models #llm #natural_language_processing #pretrained_models

The Qwen series includes powerful language models and chat models that can be used for various tasks such as chatting, content creation, information extraction, summarization, translation, coding, and more. Here are the key benefits and features Qwen offers base language models (Qwen-1.8B, Qwen-7B, Qwen-14B, Qwen-72B) and chat models (Qwen-1.8B-Chat, Qwen-7B-Chat, Qwen-14B-Chat, Qwen-72B-Chat) with different sizes and capabilities.
- **Performance** The models are available in quantized forms (Int4 and Int8) which reduce memory usage and improve inference speed without significant performance degradation.
- **System Prompt** The models can use tools, act as agents, or even interpret code, with good performance on code execution and tool-use benchmarks.
- **Long-Context Understanding** Easy deployment options include using vLLM, FastChat, Web UI demos, CLI demos, and OpenAI-style APIs.
- **Finetuning**: Scripts are provided for finetuning the models using full-parameter, LoRA, and Q-LoRA methods.

Overall, Qwen models offer robust performance, flexibility, and ease of use, making them suitable for a wide range of applications.

https://github.com/QwenLM/Qwen