model architecture AI Agent Skills

Browse 5 skills related to model architecture

distributed-llm-pretraining-torchtitan

21.8k
davila7davila7

Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.

Model ArchitectureDistributed TrainingTorchTitan+7
143 days ago

mamba-architecture

21.8k
davila7davila7

State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.

Model ArchitectureMambaState Space Models+6
143 days ago

implementing-llms-litgpt

21.8k
davila7davila7

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when needing clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

Model ArchitectureLitGPTLightning AI+9
143 days ago

rwkv-architecture

21.8k
davila7davila7

RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.

RWKVModel ArchitectureRNN+6
143 days ago

nanogpt

21.8k
davila7davila7

Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).

Model ArchitectureNanoGPTGPT-2+6
143 days ago