Examples

Hands-on Jupyter notebooks for learning Nabla from basics to compiled training loops.

All notebooks in this section are generated from the examples/*.py source files.

Example Notebooks

• Example 1: Tensors and Operations
• Example 2: Automatic Differentiation
• Example 3a: MLP Training (PyTorch-Style)
• Example 3b: MLP Training (JAX-Style / Functional)
• Example 4: Transforms and @nb.compile
• Example 5a: Transformer Training (PyTorch-Style)
• Example 5b: Transformer Training (JAX-Style / Functional)
• Example 6: MLP Pipeline Parallelism (GPipe)
• Example 7: 2D Parallel Training (PP + DP)
• Example 8: Pipeline Parallel Inference
• Example 9: Compile vs Eager vs JAX
• Example 10: LoRA Fine-Tuning MVP
• Example 11: QLoRA Fine-Tuning MVP