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