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+## Model Registry
+
+### Structure
+
+Each model is registered in a separate file within the `registry` module (e.g. `registry/_llama.py`).
+
+Within each model registration file, a high-level `ModelMeta` is created for each model version, with the following structure:
+```python
+@dataclass
+class ModelMeta:
+    org: str
+    base_name: str
+    model_version: str
+    model_info_cls: type[ModelInfo]
+    model_sizes: list[str] = field(default_factory=list)
+    instruct_tags: list[str] = field(default_factory=list)
+    quant_types: list[QuantType] | dict[str, list[QuantType]] = field(default_factory=list)
+    is_multimodal: bool = False
+```
+
+Each model then instantiates a global `ModelMeta` for its specific model version, defining how the model path (e.g. `unsloth/Llama-3.1-8B-Instruct`) is constructed since each model type has a different naming convention.
+```python
+LlamaMeta_3_1 = ModelMeta(
+    org="meta-llama",
+    base_name="Llama",
+    instruct_tags=[None, "Instruct"],
+    model_version="3.1",
+    model_sizes=["8"],
+    model_info_cls=LlamaModelInfo,
+    is_multimodal=False,
+    quant_types=[QuantType.NONE, QuantType.BNB, QuantType.UNSLOTH],
+)
+```
+
+`LlamaModelInfo` is a subclass of `ModelInfo` that defines the model path for each model size and quant type.
+```python
+class LlamaModelInfo(ModelInfo):
+    @classmethod
+    def construct_model_name(cls, base_name, version, size, quant_type, instruct_tag):
+        key = f"{base_name}-{version}-{size}B"
+        return super().construct_model_name(base_name, version, size, quant_type, instruct_tag, key)
+```
+
+Once these constructs are defined, the model is registered in the `registry` module by calling `register_models` with the `ModelMeta` and `ModelInfo` classes.
+