| from __future__ import annotations
|
|
|
| from typing import TYPE_CHECKING
|
|
|
| if TYPE_CHECKING:
|
| from torch import Tensor
|
|
|
| from .base import ModelBase, gguf
|
|
|
| from .qwen import Qwen2MoeModel
|
|
|
|
|
| @ModelBase.register("Dots1ForCausalLM")
|
| class Dots1Model(Qwen2MoeModel):
|
| model_arch = gguf.MODEL_ARCH.DOTS1
|
|
|
| def __init__(self, *args, **kwargs):
|
| super().__init__(*args, **kwargs)
|
| self.hparams["num_experts"] = self.hparams["n_routed_experts"]
|
|
|
| def set_gguf_parameters(self):
|
| super().set_gguf_parameters()
|
| self.gguf_writer.add_leading_dense_block_count(self.hparams["first_k_dense_replace"])
|
| self.gguf_writer.add_expert_shared_count(self.hparams["n_shared_experts"])
|
| self.gguf_writer.add_expert_weights_scale(self.hparams["routed_scaling_factor"])
|
| self.gguf_writer.add_expert_weights_norm(self.hparams["norm_topk_prob"])
|
|
|
| def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None):
|
| if "shared_experts" in name:
|
| yield from ModelBase.modify_tensors(self, data_torch, name, bid)
|
| else:
|
| yield from super().modify_tensors(data_torch, name, bid)
|
|
|
