llama.cpp k2-fast2: MBZUAI model/K2Horizon + FAST2 sliding-window override

c59fd93 verified about 1 month ago

933 Bytes

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))

	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))