1.2 KiB
1.2 KiB
PyTorch — reference material
Placeholder. This folder will cover PyTorch: the framework most modern AI models are written in. You don't need to know PyTorch to use a model, but you'll see it everywhere once you start poking around.
Planned topics:
- What a tensor is, and why it's basically a multi-dimensional array
- Moving tensors between CPU and GPU (and what to do if you don't have a GPU)
- Loading a pretrained model and running inference
- The shape of a forward pass, conceptually
torch.no_grad()— and when it matters- Reading a model architecture without panicking
- A very gentle intro to training and fine-tuning (separate file, optional)
- CPU-only PyTorch installs vs. CUDA installs — which one you actually want
When to dip in
When you find yourself reading model code and the lines starting with torch. are blocking you, or when you want to fine-tune something on your own data.
When not to dip in
If you only ever call models through a high-level API (Hugging Face pipeline(), an OpenAI-compatible client, etc.), you may never need this.
Prerequisites
Comfort with ../python/, especially classes and basic data structures.