Hands-on coding tutorial series for large language models with slides and runnable notebooks covering fine-tuning, prompting, RLHF, safety, steganography, watermarking, multimodal models, GUI agents, and deployment. Community-maintained, free course materials for students and researchers.
AI Deploy2024
Applies quantization, pruning, distillation, speculative decoding and sparsity to compress and accelerate deep learning models, producing exportable checkpoints ready for deployment on TensorRT‑LLM, TensorRT, vLLM and similar inference runtimes.
AI Train2024
Accelerates video generation with a unified framework for inference, finetuning, LoRA, distillation, sparse attention, and distributed execution for research and demos.
AI Train2024
Pretrained foundation model for zero-shot point and quantile forecasting on unseen time series, no per-dataset training. Decoder-only, trained on 100B real-world time-points; v2.5 (200M params) handles up to 16k context and 1k-step horizons.
AI Infra2024
Stores and reuses LLM key-value caches across GPU, CPU, disk, and remote backends so vLLM and SGLang skip recomputing repeated context. Non-prefix reuse (CacheBlend) and PD disaggregation cut time-to-first-token for long-context and RAG serving.
AI Train2024
A community speedrun to train a 124M GPT as fast as possible on 8 H100s, all chasing a fixed 3.28 FineWeb loss. Successive records cut the run from llm.c's 45 minutes to under 1.4, mostly via the new Muon optimizer rather than more hardware.
AI Model2024
Provides code, pretrained weights, and tooling for protein language models and structure prediction — including ESMC, ESMFold2, sparse autoencoders (SAEs), and the ESM Atlas. Includes model checkpoints, tutorials, Hugging Face & Biohub integration, and an MIT license.
AI Model2024
A research codebase and model family for vision–language models that experiments with data‑centric post‑training strategies and long‑context multimodal reasoning. Includes model reports, released research weights (non‑commercial), grounding tools (LocateAnything) and integrations for inference/optimization.
Official code companion to the O'Reilly book by Jay Alammar and Maarten Grootendorst: 12 chapters of runnable notebooks on tokens, embeddings, Transformers, text classification, clustering, prompt engineering, semantic search, RAG, and fine-tuning.
AI Model2024
An instruction-tuned 8B Llama 3.1 model for multilingual conversational text generation, built for assistant-style chat and long-context inputs (up to 128k tokens). Available for use via the Transformers pipeline and inference endpoints, with common optimizations like safetensors.
AI Infra2024
kvcache-ai (maintainers / MADSys group, Tsinghua University & contributors)MADSys Lab, Tsinghua University, Approaching.AI +1
Runs huge mixture-of-experts LLMs like DeepSeek-R1/V3 on a single 24GB GPU plus CPU DRAM by keeping attention on the GPU and offloading expert weights to CPU. Reports 3-28x speedups via Intel AMX/AVX512 kernels and fits 139K context in 24GB VRAM.
AI Audio2024
Local WebUI for video and audio dubbing: download YouTube, isolate vocals, transcribe with Whisper, translate into 100+ languages, and generate multilingual TTS or zero-shot voice clones. Uses Gradio, yt-dlp, Demucs, Whisper/Faster-Whisper, F5/E2/CosyVoice and Edge-TTS; Windows-focused with optional Azure integration.