A 13B large language model developed by Baichuan Intelligent Technology
- artificial-intelligence
- chatgpt
- chinese
- gpt-4
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A 13B large language model developed by Baichuan Intelligent Technology
Python 3.9 to JavaScript compiler - Lean, fast, open!
Get Keyboard,Mouse,ScreenShot,Microphone Inputs from Target Computer and Send to your Mail.
An active fork of curl-impersonate with more versions and build targets. A series of patches that make curl requests look like Chrome, Firefox and Safari.
🔎 Most Advanced Open Source Intelligence (OSINT) Framework for scanning IP Address, Emails, Websites, Organizations.
[CVPR 2023 Highlight] InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
Minimalistic large language model 3D-parallelism training
POT : Python Optimal Transport
Official Implementation of "Graph of Thoughts: Solving Elaborate Problems with Large Language Models"
Incremental merge for git
A OSINT tool to obtain a target's phone number just by having his email address
[ICRA 2026] GMR: General Motion Retargeting. Retarget human motions into diverse humanoid robots in real time on CPU. Retargeter for TWIST.
Minimal Claude Code alternative. Single Python file, zero dependencies, ~250 lines.
OpenStack Storage (Swift). Mirror of code maintained at opendev.org.
Claude Code to OpenAI API Proxy
An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
A command-line tool that helps you clean up Git branches that have been merged into master.
SOTA low-bit LLM quantization (INT8/FP8/MXFP8/INT4/MXFP4/NVFP4) & sparsity; leading model compression techniques on PyTorch, TensorFlow, and ONNX Runtime
[ECCV2024] API code for T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergy
[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
[ICCV2025] LHM: Large Animatable Human Reconstruction Model from a Single Image in Seconds
🎚️ Open Source Audio Matching and Mastering