from __future__ import annotations
from typing import Callable, TYPE_CHECKING
if TYPE_CHECKING:
from torch import Tensor
from .base import ModelBase, gguf
from .llava import LlavaVisionModel
@ModelBase.register("LightOnOCRForConditionalGeneration")
@ModelBase.example("lightonai/LightOnOCR-1B-1025")
class LightOnOCRVisionModel(LlavaVisionModel):
is_mistral_format = False
use_break_tok = False
def set_gguf_parameters(self):
super().set_gguf_parameters()
self.gguf_writer.add_clip_projector_type(gguf.VisionProjectorType.LIGHTONOCR)
@classmethod
def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
name, gen = item
name = name.replace("model.vision_encoder.", "vision_tower.")
name = name.replace("model.vision_projection.", "multi_modal_projector.")
return super().filter_tensors((name, gen))