Update eval_types.py

[borgr]

Added rnn architecture type

[damian1996]

Are you sure we are need Architecture class at all? Probably model_name and provider_name can identify the model for us and I'm not sure if we need information about underlying architecture from evaluation logging point of view.

[nelaturuharsha]

I think the way things are setup - model_name is sufficient information for a checkpoint, and there will be edge-cases like Nemotron-H which are hybrid and this class will bloat up without adding other information.

I think it might be okay to remove it completely.

[damian1996]

In my opinion, this full class is not very helpful. Architecture like Harsha mentioned can be probably removed completely. Number of parameters often is included in model_name directly. If not, there probably this information is not necessary. Context_window/instruct also is dependant on the model directly (instruct often is given in model name as well).

class Configuration(BaseModel):
    architecture: Optional[Architecture] = Field(
        None, description='Model architecture type'
    )
    parameters: Optional[conint(ge=1)] = Field(
        None, description='Number of parameters in billions'
    )
    context_window: conint(ge=1) = Field(
        ..., description='Maximum context window size in tokens'
    )
    is_instruct: Optional[bool] = Field(
        None, description='Whether the model is instruction-tuned'
    )
    hf_path: Optional[str] = Field(None, description='HuggingFace model path')
    revision: Optional[str] = Field(None, description='Model revision/commit hash')