ikawrakow/ik_llama.cpp
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Add python changes for dots1 support

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This commit is contained in:
Saood Karim
2025-07-02 21:04:15 -05:00
parent c834b6d0b0
commit eb88e8f4e7
3 changed files with 55 additions and 1 deletions
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28
convert_hf_to_gguf.py
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@@ -3850,6 +3850,34 @@ class JaisModel(Model):
self.gguf_writer.add_max_alibi_bias(self.max_alibi_bias)
@Model.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"])
if self.hparams["scoring_func"] == "noaux_tc":
self.gguf_writer.add_expert_gating_func(gguf.ExpertGatingFuncType.SIGMOID)
else:
raise ValueError(f"Unsupported scoring_func value: {self.hparams['scoring_func']}")
def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None):
if name.endswith("e_score_correction_bias"):
name = name.replace("e_score_correction_bias", "e_score_correction.bias")
if "shared_experts" in name:
return [(self.map_tensor_name(name), data_torch)]
return super().modify_tensors(data_torch, name, bid)
@Model.register("ChatGLMModel", "ChatGLMForConditionalGeneration")
class ChatGLMModel(Model):
model_arch = gguf.MODEL_ARCH.CHATGLM

26
gguf-py/gguf/constants.py
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@@ -226,6 +226,7 @@ class MODEL_ARCH(IntEnum):
T5 = auto()
T5ENCODER = auto()
JAIS = auto()
DOTS1 = auto()
class MODEL_TENSOR(IntEnum):
@@ -362,6 +363,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
MODEL_ARCH.T5: "t5",
MODEL_ARCH.T5ENCODER: "t5encoder",
MODEL_ARCH.JAIS: "jais",
MODEL_ARCH.DOTS1: "dots1",
}
TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
@@ -1164,6 +1166,30 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
MODEL_TENSOR.FFN_GATE,
MODEL_TENSOR.FFN_UP,
],
MODEL_ARCH.DOTS1: [
MODEL_TENSOR.TOKEN_EMBD,
MODEL_TENSOR.OUTPUT_NORM,
MODEL_TENSOR.OUTPUT,
MODEL_TENSOR.ATTN_NORM,
MODEL_TENSOR.ATTN_Q,
MODEL_TENSOR.ATTN_Q_NORM,
MODEL_TENSOR.ATTN_K,
MODEL_TENSOR.ATTN_K_NORM,
MODEL_TENSOR.ATTN_V,
MODEL_TENSOR.ATTN_OUT,
MODEL_TENSOR.FFN_EXP_PROBS_B,
MODEL_TENSOR.FFN_NORM,
MODEL_TENSOR.FFN_GATE,
MODEL_TENSOR.FFN_GATE_EXP,
MODEL_TENSOR.FFN_GATE_INP,
MODEL_TENSOR.FFN_GATE_SHEXP,
MODEL_TENSOR.FFN_DOWN,
MODEL_TENSOR.FFN_DOWN_EXP,
MODEL_TENSOR.FFN_DOWN_SHEXP,
MODEL_TENSOR.FFN_UP,
MODEL_TENSOR.FFN_UP_EXP,
MODEL_TENSOR.FFN_UP_SHEXP,
],
# TODO
}

2
gguf-py/gguf/tensor_mapping.py
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@@ -257,7 +257,7 @@ class TensorNameMap:
),
MODEL_TENSOR.FFN_EXP_PROBS_B: (
"model.layers.{bid}.mlp.gate.e_score_correction", # deepseek-v3
"model.layers.{bid}.mlp.gate.e_score_correction", # deepseek-v3 dots1
),
# Feed-forward up