# `Latu.ML.Model`
[🔗](https://github.com/zero-one-group/latu_ml/blob/v0.4.2/lib/latu/ml/model.ex#L1)

A fitted model: a reference into the session's ML cache, and the context needed to use it.

**Not a value.** The model itself lives on the server, in a cache that offloads it to disk
when memory is tight and evicts it when the session ends — so a `%Latu.ML.Model{}` can name
something that is no longer there, and every verb that touches one can fail for that reason.
`Latu.ML.with_model/3` is the bracket; `Latu.ML.delete/1` is the explicit release. There is no
finalizer, because BEAM terms have none.

`dataset` is the plan the model was fitted on, kept so a summary the server has evicted can
be rebuilt from it. It is nil for a model from `Latu.ML.load/3`, which was not fitted here —
and which has no summary on the server either, because a model's save format does not carry
one. `uid` is the client's, copied from the estimator: a `Fit` answers with an `obj_ref` and
nothing else. A loaded model's is the one the saved metadata held, which is the only command
that gives a uid back.

`class` is nil for a model whose estimator can fit more than one — `LDA` returns a
`LocalLDAModel` or a `DistributedLDAModel` depending on its `optimizer`, and a `Fit` does not
say which. `candidates` is then both of them, and is what an attribute is looked up in;
nothing claims a class it cannot know.

# `t`

```elixir
@type t() :: %Latu.ML.Model{
  candidates: [String.t()],
  class: String.t() | nil,
  dataset: term(),
  params: [Latu.ML.Plan.param()],
  ref: Latu.ML.Plan.object_ref(),
  session: Latu.Session.t(),
  uid: String.t() | nil
}
```

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*Consult [api-reference.md](api-reference.md) for complete listing*