1.p-e-w / heretic
Training-free language model modification: Remove censorship, suppress slop, reduce sycophancy, and more
Ranked by Attention Score: stars gained over the last 7 complete days
28 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
Training-free language model modification: Remove censorship, suppress slop, reduce sycophancy, and more
A high-throughput and memory-efficient inference and serving engine for LLMs
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Faster Whisper transcription with CTranslate2
SGLang is a high-performance serving framework for large language models and multimodal models.
Port of OpenAI's Whisper model in C/C++
零基础入门大模型(LLM)的基础教程:从零手写 GPT-2,一行行看懂大模型是怎么工作的 | Build GPT-2 from scratch in PyTorch, step by step
SOTA Open Source TTS
Nano vLLM
A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.
MNN: A blazing-fast, lightweight inference engine battle-tested by Alibaba, powering high-performance on-device LLMs and Edge AI.
A framework for few-shot evaluation of language models.
邱锡鹏《神经网络与深度学习》第二版与通识版:电子书、章节目录、学习资源与勘误。
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Translate manga/image 一键翻译各类图片内文字 https://cotrans.touhou.ai/ (no longer working)
《李宏毅深度学习教程》(李宏毅老师推荐👍,苹果书🍎),PDF下载地址:https://github.com/datawhalechina/leedl-tutorial/releases
CVPR 2026 论文和开源项目合集
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
免選字的注音輸入法:在本機用 Transformer 看前文選字。支援 Linux(Fcitx5/IBus)、macOS、Windows。
OpenMMLab Detection Toolbox and Benchmark
Scalable and user friendly neural :brain: forecasting algorithms.
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
Foundation Models for Genomics & Transcriptomics
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)
Neural question generation using transformers
allRank is a framework for training learning-to-rank neural models based on PyTorch.