Kopitiam Runtime: native model file loaders.

This crate turns a GGUF or SafeTensors file on disk into a format-agnostic description of what it contains: model-level hyperparameters ([ModelMetadata]) and a directory of tensors, each described by name, [kopitiam_core::DType], [kopitiam_core::Shape], and its raw on-disk bytes ([TensorEntry], served through [LoadedModel::tensor_bytes]).

Why this crate never constructs a Tensor

kopitiam-tensor — the crate that owns the Tensor type — is being developed independently of this one. Depending on it here would couple two crates whose APIs are each still settling, for a feature this crate does not need: nothing a loader does requires an actual Tensor, only the bytes, dtype and shape needed to build one. So this crate stops one step short: [LoadedModel::tensor_bytes] hands back exactly those bytes, and whoever does depend on kopitiam-tensor combines them with the dtype and shape from [LoadedModel::tensor] to build the tensor on their side of the boundary. Neither crate has to know the other's internals for this to work.

Supported formats

• GGUF ([GgufLoader], module gguf) — the llama.cpp/ggml format. Note its on-disk dimension order is the reverse of this crate's [kopitiam_core::Shape] convention; see the gguf module docs before touching anything shape-related there.
• SafeTensors ([SafeTensorsLoader], module safetensors) — Hugging Face's format. Its dimension order already matches Shape's convention directly.

[load_model] picks between the two by sniffing file content (GGUF has a magic number; SafeTensors does not, so it is the fallback), so most callers only need that one function.

Memory strategy

Model files are memory-mapped where possible rather than read fully into a Vec<u8> — see the internal byte_source module's doc for why that matters at multi-gigabyte model sizes and when this crate falls back to a plain read instead.

Malformed input

Every parser in this crate treats its input as untrusted: truncated files, offsets that point past end-of-file, and absurd counts that would otherwise justify a huge allocation all become [kopitiam_core::Error::MalformedModel] rather than a panic. A tensor type or dtype this crate cannot represent becomes [kopitiam_core::Error::UnsupportedModelFeature] instead of being silently misdecoded as something else.