Take full ownership of model weights. Master low-rank matrix decomposition, 4-bit normal float quantization, ultra-efficient Unsloth training loops, and preference alignment via DPO without RL reward models.
The mathematical derivation that made fine-tuning 100x cheaper.
Accelerate training with Unsloth and custom autograd kernels.
Align models with human preferences without training complex reward models.