| """Local model registry for GPT-2 LLM2Vec integration.""" | |
| from __future__ import annotations | |
| from typing import Type | |
| from transformers import PreTrainedModel | |
| from gpt2_llm2vec.models.bidirectional_gpt2 import GPT2BiForMNTP | |
| MODEL_REGISTRY: dict[str, Type[PreTrainedModel]] = { | |
| "gpt2": GPT2BiForMNTP, | |
| "gpt2-medium": GPT2BiForMNTP, | |
| "gpt2-large": GPT2BiForMNTP, | |
| "gpt2-xl": GPT2BiForMNTP, | |
| } | |
| def get_model_class(model_name_or_path: str) -> Type[PreTrainedModel]: | |
| """Return a registered model class for a given model name/path.""" | |
| key = model_name_or_path.lower() | |
| if key in MODEL_REGISTRY: | |
| return MODEL_REGISTRY[key] | |
| # Fallback: if user passes a local path/name containing "gpt2" | |
| if "gpt2" in key: | |
| return GPT2BiForMNTP | |
| raise ValueError( | |
| f"Unsupported model '{model_name_or_path}'. " | |
| f"Supported keys: {sorted(MODEL_REGISTRY.keys())}" | |
| ) | |