from __future__ import annotations
from typing import Callable, TYPE_CHECKING
if TYPE_CHECKING:
from torch import Tensor
from .base import ModelBase, gguf
from .llama import LlamaModel
from .qwenvl import Qwen2VLVisionModel
@ModelBase.register("Sarashina2VisionForCausalLM")
@ModelBase.example("sbintuitions/sarashina2.2-vision-3b")
class Sarashina2VLTextModel(LlamaModel):
model_arch = gguf.MODEL_ARCH.LLAMA
@classmethod
def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
name, gen = item
if name.startswith("llm."):
name = name.replace("llm.", "", 1)
elif name.startswith("norm."):
return None
return super().filter_tensors((name, gen))
@ModelBase.register("Sarashina2VisionForCausalLM")
@ModelBase.example("sbintuitions/sarashina2.2-vision-3b")
class Sarashina2VLVisionModel(Qwen2VLVisionModel):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.global_config['model_type'] = "qwen2_vl"