transformer
62 proyectos comparten este topic de GitHub
Las líneas conectan a los miembros que están mediblemente relacionados entre sí. El tamaño de los puntos refleja las estrellas.
🧬 Miembros
transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text,…
★ 168.2k
vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
★ 95.7k
sglang
SGLang is a high-performance serving framework for large language models and multimodal models.
★ 38.2k
heretic
Fully automatic censorship removal for language models
★ 36.6k
MNN
MNN: A blazing-fast, lightweight inference engine battle-tested by Alibaba, powering high-performance…
★ 16.3k
nano-vllm
Nano vLLM
★ 16.2k
RWKV-LM
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT…
★ 14.8k
lm-evaluation-harness
A framework for few-shot evaluation of language models.
★ 14.3k
petals
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
★ 10.7k
kimi-k3-in-c
A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS,…
★ 9.2k
MindSearch
🔍 An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)
★ 6.9k
FasterTransformer
Transformer related optimization, including BERT, GPT
★ 6.4k
semantic-router
An open, programmable decision layer for models and compute.
★ 6.3k
cactus
Quantization, kernels, runtime and inference engine for mobiles, wearables, smart home and robots.
★ 6.2k
AIGC-Interview-Book
★ 5.1k
beat-ai
★ 4.7k
beat-ai
★ 4.7k
beat-ai
★ 4.7k
beatai
★ 4.7k
towhee
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
★ 3.5k
vllm-ascend
Community maintained hardware plugin for vLLM on Huawei Ascend
★ 3k
ai-engineering-resources
Research papers and blogs to transition to AI Engineering
★ 2.7k
mPLUG-Owl
mPLUG-Owl: The Powerful Multi-modal Large Language Model Family
★ 2.5k
EasyLM
Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning,…
★ 2.5k
MoBA
MoBA: Mixture of Block Attention for Long-Context LLMs
★ 2.2k
Awesome-LLM-Long-Context-Modeling
📰 Must-read papers and blogs on LLM based Long Context Modeling 🔥
★ 2.2k
aici
AICI: Prompts as (Wasm) Programs
★ 2.1k
FireRedASR
Open-source industrial-grade ASR models supporting Mandarin, Chinese dialects and English, achieving a new…
★ 2k
LLMCompiler
[ICML 2024] LLMCompiler: An LLM Compiler for Parallel Function Calling
★ 1.9k
graph-fraud-detection-papers
A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources
★ 1.9k
nndeploy
一款简单易用和高性能的AI部署框架 | An Easy-to-Use and High-Performance AI Deployment Framework
★ 1.9k
diy-llm
Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference &…
★ 1.9k · GitHub ↗
safe-rlhf
Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback
★ 1.6k
VibeThinker
Tiny Model, Big Logic: Diversity-Driven Optimization Elicits Large-Model Reasoning Ability in VibeThinker-1.5B
★ 1.6k
parallax
Parallax is a distributed model serving framework that lets you build your own AI cluster anywhere
★ 1.4k
GPA
[AutoArk] GPA (General Purpose Audio) can do ASR, TTS and voice conversion with one tiny model!
★ 1.3k
TinyEngram
Research of DeepSeek Engram Architecture based on Qwen-3 and Stable Diffusion series.
★ 1.1k
CogView2
official code repo for paper "CogView2: Faster and Better Text-to-Image Generation via Hierarchical…
★ 955
papers-for-molecular-design-using-DL
List of Molecular and Material design using Generative AI and Deep Learning
★ 951
GenAI_LLM_timeline
ChatGPT, GenerativeAI and LLMs Timeline
★ 948
YOLOS
[NeurIPS 2021] You Only Look at One Sequence
★ 903
Spark-X2.6
Spark-x2.6 open model series. Pushing the Limits of Agentic Capabilities in On-Device Models
★ 860 · GitHub ↗
kat
[ICLR2025] Kolmogorov-Arnold Transformer
★ 847
HiVT
[CVPR 2022] HiVT: Hierarchical Vector Transformer for Multi-Agent Motion Prediction
★ 745
SqueezeLLM
[ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization
★ 725
diffusion-forcing-transformer
[ICML 2025] Official PyTorch Implementation of "History-Guided Video Diffusion"
★ 709
InterFuser
[CoRL 2022] InterFuser: Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer
★ 653
vidur
Accurate, large-scale, and extensible simulator for LLM inference Systems
★ 642
multilspy
multilspy is a lsp client library in Python intended to be used to build applications around language servers.
★ 613
memit
Mass-editing thousands of facts into a transformer memory (ICLR 2023)
★ 555
krasis
Krasis is a Hybrid LLM runtime which focuses on efficient running of larger models on consumer grade VRAM…
★ 522
JetStream
JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs…
★ 470
SparseBEV
[ICCV 2023 & TPAMI 2026] SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos
★ 468
KVQuant
[NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
★ 437
KIVI
[ICML 2024] KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache
★ 435
Awesome-Attention-Heads
An awesome repository & A comprehensive survey on interpretability of LLM attention heads.
★ 414
OpenGraph
[EMNLP'2024] "OpenGraph: Towards Open Graph Foundation Models"
★ 337
chat.petals.dev
💬 Chatbot web app + HTTP and Websocket endpoints for LLM inference with the Petals client
★ 321
cevahir-ai
Full-stack open-source AI engine for building language models — tokenizer training, transformer…
★ 246
hands-on-llm
动手学大模型全栈：CS336 中文精讲 · PyTorch 手搓 Transformer · 单卡复现…
★ 119 · GitHub ↗
neo-unify
Toy-scale unified multimodal model experiments — encoder-free understanding & generation with…
★ 51
TeaLeaves
End-to-end pipeline for seeing how LLMs actually process your prompts. Capture attention across every layer,…
★ 44
🔗 Familias relacionadas
Medido a partir de los temas de GitHub compartidos por ambos proyectos, ponderado por cuán raros son cada uno de los temas.