34 lines
933 B
Python
34 lines
933 B
Python
|
from __future__ import annotations
|
||
|
|
|
||
|
|
from typing import Callable, TYPE_CHECKING
|
||
|
|
|
||
|
|
if TYPE_CHECKING:
|
||
|
|
from torch import Tensor
|
||
|
|
|
||
|
|
from .base import MmprojModel, ModelBase, gguf
|
||
|
|
|
||
|
|
from .llama import LlamaModel
|
||
|
|
|
||
|
|
|
||
|
|
@ModelBase.register("CogVLMForCausalLM")
|
||
|
|
class CogVLMVisionModel(MmprojModel):
|
||
|
|
|
||
|
|
def set_gguf_parameters(self):
|
||
|
|
super().set_gguf_parameters()
|
||
|
|
self.gguf_writer.add_vision_attention_layernorm_eps(self.hparams.get("layer_norm_eps", 1e-6))
|
||
|
|
self.gguf_writer.add_clip_projector_type(gguf.VisionProjectorType.COGVLM)
|
||
|
|
|
||
|
|
@classmethod
|
||
|
|
def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
|
||
|
|
name, gen = item
|
||
|
|
|
||
|
|
if not name.startswith("model.vision."):
|
||
|
|
return None
|
||
|
|
|
||
|
|
return super().filter_tensors(item)
|
||
|
|
|
||
|
|
|
||
|
|
@ModelBase.register("CogVLMForCausalLM")
|
||
|
|
class CogVLMModel(LlamaModel):
|
||
|
|
model_arch = gguf.MODEL_ARCH.COGVLM
|