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model: support GLM MoE DSA arch (NOTE: indexer is not yet supported) #19460

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ngxson merged 10 commits into from
Feb 13, 2026
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model: support GLM MoE DSA arch (NOTE: indexer is not yet supported) #19460

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cc0d6c2
model: support GLM MoE DSA arch
ngxson Feb 9, 2026
a44a3db
working version
ngxson Feb 9, 2026
0451c84
pyright
ngxson Feb 9, 2026
9e4e556
keep indexer tensors
ngxson Feb 11, 2026
64184c1
add indexer gguf params
ngxson Feb 12, 2026
d8a4656
loaded now
ngxson Feb 12, 2026
9bfafad
Apply suggestions from code review
ngxson Feb 12, 2026
8255401
update
ngxson Feb 12, 2026
7b23cd9
Update src/llama-model.cpp
ngxson Feb 12, 2026
1daef5f
minor fix and cleanup
CISC Feb 13, 2026
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92 changes: 54 additions & 38 deletions convert_hf_to_gguf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1605,6 +1605,23 @@ def _set_vocab_glmedge(self):
special_vocab._set_special_token("bos", tokenizer.get_added_vocab()["<|endoftext|>"])
special_vocab.add_to_gguf(self.gguf_writer)

def _set_vocab_glm(self):
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(self.dir_model)
special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=True)
tokens, toktypes, tokpre = self.get_vocab_base()
self.gguf_writer.add_tokenizer_model("gpt2")
self.gguf_writer.add_tokenizer_pre(tokpre)
self.gguf_writer.add_token_list(tokens)
self.gguf_writer.add_token_types(toktypes)
# Special tokens
# Note: Using <|endoftext|> (151329) for eot causes endless generation
special_vocab._set_special_token("bos", tokenizer.get_added_vocab()["[gMASK]"]) # 151331
special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"]) # 151336
special_vocab._set_special_token("unk", tokenizer.get_added_vocab()["<|endoftext|>"]) # 151329
special_vocab._set_special_token("eom", tokenizer.get_added_vocab()["<|observation|>"]) # 151338
special_vocab.add_to_gguf(self.gguf_writer)

def _set_vocab_interns1(self):
tokens: list[str] = []
toktypes: list[int] = []
Expand Down Expand Up @@ -7585,6 +7602,9 @@ def prepare_tensors(self):
class DeepseekV2Model(TextModel):
model_arch = gguf.MODEL_ARCH.DEEPSEEK2

# TODO @ngxson : remove this when we support MTP for deepseek models
skip_mtp = True

def set_vocab(self):
try:
self._set_vocab_gpt2()
Expand Down Expand Up @@ -7716,10 +7736,11 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter
name = name.replace("e_score_correction_bias", "e_score_correction.bias")

# skip Multi-Token Prediction (MTP) layers
block_count = self.hparams["num_hidden_layers"]
match = re.match(r"model.layers.(\d+)", name)
if match and int(match.group(1)) >= block_count:
return
if self.skip_mtp:
block_count = self.hparams["num_hidden_layers"]
match = re.match(r"model.layers.(\d+)", name)
if match and int(match.group(1)) >= block_count:
return

# process the experts separately
if name.find("mlp.experts") != -1:
Expand Down Expand Up @@ -8559,24 +8580,7 @@ def __init__(self, *args, **kwargs):
self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)

def set_vocab(self):
from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained(self.dir_model)
special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=True)
tokens, toktypes, tokpre = self.get_vocab_base()
self.gguf_writer.add_tokenizer_model("gpt2")
self.gguf_writer.add_tokenizer_pre(tokpre)
self.gguf_writer.add_token_list(tokens)
self.gguf_writer.add_token_types(toktypes)

# Special tokens
# Note: Using <|endoftext|> (151329) for eot causes endless generation
special_vocab._set_special_token("bos", tokenizer.get_added_vocab()["[gMASK]"]) # 151331
special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"]) # 151336
special_vocab._set_special_token("unk", tokenizer.get_added_vocab()["<|endoftext|>"]) # 151329
special_vocab._set_special_token("eom", tokenizer.get_added_vocab()["<|observation|>"]) # 151338

special_vocab.add_to_gguf(self.gguf_writer)
return self._set_vocab_glm()

def set_gguf_parameters(self):
super().set_gguf_parameters()
Expand Down Expand Up @@ -8676,26 +8680,38 @@ def prepare_tensors(self):
class Glm4MoeLiteModel(DeepseekV2Model):
model_arch = gguf.MODEL_ARCH.DEEPSEEK2

# copied from Glm4MoeModel
def set_vocab(self):
from transformers import AutoTokenizer
return self._set_vocab_glm()

tokenizer = AutoTokenizer.from_pretrained(self.dir_model)
special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=True)
tokens, toktypes, tokpre = self.get_vocab_base()
self.gguf_writer.add_tokenizer_model("gpt2")
self.gguf_writer.add_tokenizer_pre(tokpre)
self.gguf_writer.add_token_list(tokens)
self.gguf_writer.add_token_types(toktypes)

# Special tokens
# Note: Using <|endoftext|> (151329) for eot causes endless generation
special_vocab._set_special_token("bos", tokenizer.get_added_vocab()["[gMASK]"]) # 151331
special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"]) # 151336
special_vocab._set_special_token("unk", tokenizer.get_added_vocab()["<|endoftext|>"]) # 151329
special_vocab._set_special_token("eom", tokenizer.get_added_vocab()["<|observation|>"]) # 151338
@ModelBase.register("GlmMoeDsaForCausalLM")
class GlmMoeDsaModel(DeepseekV2Model):
model_arch = gguf.MODEL_ARCH.GLM_DSA
skip_mtp = False

special_vocab.add_to_gguf(self.gguf_writer)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.block_count = self.hparams["num_hidden_layers"] + self.hparams.get("num_nextn_predict_layers", 0)
self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)

def set_vocab(self):
return self._set_vocab_glm()

def set_gguf_parameters(self):
super().set_gguf_parameters()

rope_dim = self.hparams["qk_rope_head_dim"]
partial_rotary_factor = self.hparams.get("partial_rotary_factor", 1.0)
self.gguf_writer.add_rope_dimension_count(int(rope_dim * partial_rotary_factor))

# NextN/MTP prediction layers
if (num_nextn_predict_layers := self.hparams.get("num_nextn_predict_layers")) is not None:
self.gguf_writer.add_nextn_predict_layers(num_nextn_predict_layers)

# DSA indexer parameters
self.gguf_writer.add_indexer_head_count(self.hparams["index_n_heads"])
self.gguf_writer.add_indexer_key_length(self.hparams["index_head_dim"])
self.gguf_writer.add_indexer_top_k(self.hparams["index_topk"])


@ModelBase.register("GlmForCausalLM", "ChatGLMModel", "ChatGLMForConditionalGeneration")
Expand Down
56 changes: 56 additions & 0 deletions gguf-py/gguf/constants.py
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Expand Up @@ -180,6 +180,11 @@ class Attention:
SLIDING_WINDOW_PATTERN = "{arch}.attention.sliding_window_pattern"
TEMPERATURE_SCALE = "{arch}.attention.temperature_scale"

class Indexer:
HEAD_COUNT = "{arch}.attention.indexer.head_count"
KEY_LENGTH = "{arch}.attention.indexer.key_length"
TOP_K = "{arch}.attention.indexer.top_k"

class Rope:
DIMENSION_COUNT = "{arch}.rope.dimension_count"
DIMENSION_SECTIONS = "{arch}.rope.dimension_sections"
Expand Down Expand Up @@ -422,6 +427,7 @@ class MODEL_ARCH(IntEnum):
CHATGLM = auto()
GLM4 = auto()
GLM4_MOE = auto()
GLM_DSA = auto()
BITNET = auto()
T5 = auto()
T5ENCODER = auto()
Expand Down Expand Up @@ -666,6 +672,10 @@ class MODEL_TENSOR(IntEnum):
VISEXP_GATE = auto()
VISEXP_DOWN = auto()
VISEXP_UP = auto()
INDEXER_K_NORM = auto()
INDEXER_PROJ = auto()
INDEXER_ATTN_K = auto()
INDEXER_ATTN_Q_B = auto()
# vision
V_MMPROJ = auto()
V_MMPROJ_FC = auto()
Expand Down Expand Up @@ -852,6 +862,7 @@ class MODEL_TENSOR(IntEnum):
MODEL_ARCH.CHATGLM: "chatglm",
MODEL_ARCH.GLM4: "glm4",
MODEL_ARCH.GLM4_MOE: "glm4moe",
MODEL_ARCH.GLM_DSA: "glm-dsa",
MODEL_ARCH.BITNET: "bitnet",
MODEL_ARCH.T5: "t5",
MODEL_ARCH.T5ENCODER: "t5encoder",
Expand Down Expand Up @@ -1094,6 +1105,10 @@ class MODEL_TENSOR(IntEnum):
MODEL_TENSOR.VISEXP_GATE: "blk.{bid}.vis_gate",
MODEL_TENSOR.VISEXP_DOWN: "blk.{bid}.vis_down",
MODEL_TENSOR.VISEXP_UP: "blk.{bid}.vis_up",
MODEL_TENSOR.INDEXER_K_NORM: "blk.{bid}.indexer.k_norm",
MODEL_TENSOR.INDEXER_PROJ: "blk.{bid}.indexer.proj",
MODEL_TENSOR.INDEXER_ATTN_K: "blk.{bid}.indexer.attn_k",
MODEL_TENSOR.INDEXER_ATTN_Q_B: "blk.{bid}.indexer.attn_q_b",
# vision
MODEL_TENSOR.V_MMPROJ: "mm.{bid}",
MODEL_TENSOR.V_MMPROJ_FC: "mm.model.fc",
Expand Down Expand Up @@ -2615,6 +2630,47 @@ class MODEL_TENSOR(IntEnum):
MODEL_TENSOR.NEXTN_SHARED_HEAD_HEAD,
MODEL_TENSOR.NEXTN_SHARED_HEAD_NORM,
],
MODEL_ARCH.GLM_DSA: [
MODEL_TENSOR.TOKEN_EMBD,
MODEL_TENSOR.OUTPUT_NORM,
MODEL_TENSOR.OUTPUT,
MODEL_TENSOR.ROPE_FREQS,
MODEL_TENSOR.ATTN_NORM,
MODEL_TENSOR.ATTN_Q,
MODEL_TENSOR.ATTN_Q_A,
MODEL_TENSOR.ATTN_Q_B,
MODEL_TENSOR.ATTN_KV_A_MQA,
MODEL_TENSOR.ATTN_KV_B,
MODEL_TENSOR.ATTN_K_B,
MODEL_TENSOR.ATTN_V_B,
MODEL_TENSOR.ATTN_Q_A_NORM,
MODEL_TENSOR.ATTN_KV_A_NORM,
MODEL_TENSOR.ATTN_OUT,
MODEL_TENSOR.ATTN_ROT_EMBD,
MODEL_TENSOR.FFN_GATE_INP,
MODEL_TENSOR.FFN_NORM,
MODEL_TENSOR.FFN_GATE,
MODEL_TENSOR.FFN_DOWN,
MODEL_TENSOR.FFN_UP,
MODEL_TENSOR.FFN_GATE_EXP,
MODEL_TENSOR.FFN_DOWN_EXP,
MODEL_TENSOR.FFN_UP_EXP,
MODEL_TENSOR.FFN_GATE_SHEXP,
MODEL_TENSOR.FFN_DOWN_SHEXP,
MODEL_TENSOR.FFN_UP_SHEXP,
MODEL_TENSOR.FFN_EXP_PROBS_B,
MODEL_TENSOR.INDEXER_K_NORM,
MODEL_TENSOR.INDEXER_PROJ,
MODEL_TENSOR.INDEXER_ATTN_K,
MODEL_TENSOR.INDEXER_ATTN_Q_B,
# NextN/MTP tensors - preserved but unused
MODEL_TENSOR.NEXTN_EH_PROJ,
MODEL_TENSOR.NEXTN_EMBED_TOKENS,
MODEL_TENSOR.NEXTN_ENORM,
MODEL_TENSOR.NEXTN_HNORM,
MODEL_TENSOR.NEXTN_SHARED_HEAD_HEAD,
MODEL_TENSOR.NEXTN_SHARED_HEAD_NORM,
],
MODEL_ARCH.BITNET: [
MODEL_TENSOR.ATTN_Q,
MODEL_TENSOR.ATTN_K,
Expand Down
9 changes: 9 additions & 0 deletions gguf-py/gguf/gguf_writer.py
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Expand Up @@ -768,6 +768,15 @@ def add_key_length_mla(self, length: int) -> None:
def add_value_length_mla(self, length: int) -> None:
self.add_uint32(Keys.Attention.VALUE_LENGTH_MLA.format(arch=self.arch), length)

def add_indexer_head_count(self, count: int) -> None:
self.add_uint32(Keys.Attention.Indexer.HEAD_COUNT.format(arch=self.arch), count)

def add_indexer_key_length(self, length: int) -> None:
self.add_uint32(Keys.Attention.Indexer.KEY_LENGTH.format(arch=self.arch), length)

def add_indexer_top_k(self, top_k: int) -> None:
self.add_uint32(Keys.Attention.Indexer.TOP_K.format(arch=self.arch), top_k)

def add_max_alibi_bias(self, bias: float) -> None:
self.add_float32(Keys.Attention.MAX_ALIBI_BIAS.format(arch=self.arch), bias)

Expand Down
16 changes: 16 additions & 0 deletions gguf-py/gguf/tensor_mapping.py
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Expand Up @@ -1199,6 +1199,22 @@ class TensorNameMap:
"model.layers.{bid}.self_attn.vision_expert_query_key_value", # cogvlm
),

MODEL_TENSOR.INDEXER_K_NORM: (
"model.layers.{bid}.self_attn.indexer.k_norm", # DSA
),

MODEL_TENSOR.INDEXER_PROJ: (
"model.layers.{bid}.self_attn.indexer.weights_proj", # DSA
),

MODEL_TENSOR.INDEXER_ATTN_K: (
"model.layers.{bid}.self_attn.indexer.wk", # DSA
),

MODEL_TENSOR.INDEXER_ATTN_Q_B: (
"model.layers.{bid}.self_attn.indexer.wq_b", # DSA
),

############################################################################
# TODO: these do not belong to block_mappings_cfg - move them to mappings_cfg
MODEL_TENSOR.ENC_OUTPUT_NORM: (
Expand Down
52 changes: 52 additions & 0 deletions src/llama-arch.cpp
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Expand Up @@ -72,6 +72,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
{ LLM_ARCH_CHATGLM, "chatglm" },
{ LLM_ARCH_GLM4, "glm4" },
{ LLM_ARCH_GLM4_MOE, "glm4moe" },
{ LLM_ARCH_GLM_DSA, "glm-dsa" },
{ LLM_ARCH_BITNET, "bitnet" },
{ LLM_ARCH_T5, "t5" },
{ LLM_ARCH_T5ENCODER, "t5encoder" },
Expand Down Expand Up @@ -222,6 +223,9 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
{ LLM_KV_ATTENTION_TEMPERATURE_SCALE, "%s.attention.temperature_scale" },
{ LLM_KV_ATTENTION_KEY_LENGTH_MLA, "%s.attention.key_length_mla" },
{ LLM_KV_ATTENTION_VALUE_LENGTH_MLA, "%s.attention.value_length_mla" },
{ LLM_KV_ATTENTION_INDEXER_HEAD_COUNT, "%s.attention.indexer.head_count" },
{ LLM_KV_ATTENTION_INDEXER_KEY_LENGTH, "%s.attention.indexer.key_length" },
{ LLM_KV_ATTENTION_INDEXER_TOP_K, "%s.attention.indexer.top_k" },

{ LLM_KV_ROPE_DIMENSION_COUNT, "%s.rope.dimension_count" },
{ LLM_KV_ROPE_DIMENSION_SECTIONS, "%s.rope.dimension_sections" },
Expand Down Expand Up @@ -512,6 +516,10 @@ static const std::map<llm_tensor, const char *> LLM_TENSOR_NAMES = {
{ LLM_TENSOR_VISEXP_FFN_GATE, "blk.%d.vis_gate" },
{ LLM_TENSOR_VISEXP_FFN_DOWN, "blk.%d.vis_down" },
{ LLM_TENSOR_VISEXP_FFN_UP, "blk.%d.vis_up" },
{ LLM_TENSOR_INDEXER_K_NORM, "blk.%d.indexer.k_norm" },
{ LLM_TENSOR_INDEXER_PROJ, "blk.%d.indexer.proj" },
{ LLM_TENSOR_INDEXER_ATTN_K, "blk.%d.indexer.attn_k" },
{ LLM_TENSOR_INDEXER_ATTN_Q_B, "blk.%d.indexer.attn_q_b" },
};

static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
Expand Down Expand Up @@ -1597,6 +1605,46 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
LLM_TENSOR_NEXTN_SHARED_HEAD_HEAD,
LLM_TENSOR_NEXTN_SHARED_HEAD_NORM,
};
case LLM_ARCH_GLM_DSA:
return {
LLM_TENSOR_TOKEN_EMBD,
LLM_TENSOR_OUTPUT_NORM,
LLM_TENSOR_OUTPUT,
LLM_TENSOR_ATTN_NORM,
LLM_TENSOR_ATTN_Q_A_NORM,
LLM_TENSOR_ATTN_KV_A_NORM,
LLM_TENSOR_ATTN_Q,
LLM_TENSOR_ATTN_Q_A,
LLM_TENSOR_ATTN_Q_B,
LLM_TENSOR_ATTN_KV_A_MQA,
LLM_TENSOR_ATTN_KV_B,
LLM_TENSOR_ATTN_K_B,
LLM_TENSOR_ATTN_V_B,
LLM_TENSOR_ATTN_OUT,
LLM_TENSOR_FFN_NORM,
LLM_TENSOR_FFN_GATE,
LLM_TENSOR_FFN_UP,
LLM_TENSOR_FFN_DOWN,
LLM_TENSOR_FFN_GATE_INP,
LLM_TENSOR_FFN_GATE_EXPS,
LLM_TENSOR_FFN_DOWN_EXPS,
LLM_TENSOR_FFN_UP_EXPS,
LLM_TENSOR_FFN_GATE_INP_SHEXP,
LLM_TENSOR_FFN_GATE_SHEXP,
LLM_TENSOR_FFN_DOWN_SHEXP,
LLM_TENSOR_FFN_UP_SHEXP,
LLM_TENSOR_FFN_EXP_PROBS_B,
LLM_TENSOR_INDEXER_K_NORM,
LLM_TENSOR_INDEXER_PROJ,
LLM_TENSOR_INDEXER_ATTN_K,
LLM_TENSOR_INDEXER_ATTN_Q_B,
LLM_TENSOR_NEXTN_EH_PROJ,
LLM_TENSOR_NEXTN_EMBED_TOKENS,
LLM_TENSOR_NEXTN_ENORM,
LLM_TENSOR_NEXTN_HNORM,
LLM_TENSOR_NEXTN_SHARED_HEAD_HEAD,
LLM_TENSOR_NEXTN_SHARED_HEAD_NORM,
};
case LLM_ARCH_BITNET:
return {
LLM_TENSOR_TOKEN_EMBD,
Expand Down Expand Up @@ -2582,6 +2630,10 @@ static const std::map<llm_tensor, llm_tensor_info> LLM_TENSOR_INFOS = {
{LLM_TENSOR_VISEXP_FFN_GATE, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
{LLM_TENSOR_VISEXP_FFN_DOWN, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
{LLM_TENSOR_VISEXP_FFN_UP, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
{LLM_TENSOR_INDEXER_K_NORM, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
{LLM_TENSOR_INDEXER_PROJ, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
{LLM_TENSOR_INDEXER_ATTN_K, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
{LLM_TENSOR_INDEXER_ATTN_Q_B, {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
// NextN/MTP tensors are currently ignored (reserved for future MTP support)
// These tensors only exist in the last layer(s) and are treated as output tensors
{LLM_TENSOR_NEXTN_EH_PROJ, {LLM_TENSOR_LAYER_OUTPUT, GGML_OP_MUL_MAT}},
Expand Down
8 changes: 8 additions & 0 deletions src/llama-arch.h
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Expand Up @@ -76,6 +76,7 @@ enum llm_arch {
LLM_ARCH_CHATGLM,
LLM_ARCH_GLM4,
LLM_ARCH_GLM4_MOE,
LLM_ARCH_GLM_DSA,
LLM_ARCH_BITNET,
LLM_ARCH_T5,
LLM_ARCH_T5ENCODER,
Expand Down Expand Up @@ -226,6 +227,9 @@ enum llm_kv {
LLM_KV_ATTENTION_TEMPERATURE_SCALE,
LLM_KV_ATTENTION_KEY_LENGTH_MLA,
LLM_KV_ATTENTION_VALUE_LENGTH_MLA,
LLM_KV_ATTENTION_INDEXER_HEAD_COUNT,
LLM_KV_ATTENTION_INDEXER_KEY_LENGTH,
LLM_KV_ATTENTION_INDEXER_TOP_K,

LLM_KV_ROPE_DIMENSION_COUNT,
LLM_KV_ROPE_DIMENSION_SECTIONS,
Expand Down Expand Up @@ -513,6 +517,10 @@ enum llm_tensor {
LLM_TENSOR_VISEXP_FFN_GATE,
LLM_TENSOR_VISEXP_FFN_DOWN,
LLM_TENSOR_VISEXP_FFN_UP,
LLM_TENSOR_INDEXER_K_NORM,
LLM_TENSOR_INDEXER_PROJ,
LLM_TENSOR_INDEXER_ATTN_K,
LLM_TENSOR_INDEXER_ATTN_Q_B,
LLM_TENSOR_NEXTN_EH_PROJ,
LLM_TENSOR_NEXTN_EMBED_TOKENS,
LLM_TENSOR_NEXTN_ENORM,
Expand Down
5 changes: 5 additions & 0 deletions src/llama-hparams.h
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Expand Up @@ -194,6 +194,11 @@ struct llama_hparams {
std::array<float, LLAMA_MAX_LAYERS> xielu_beta;
std::array<float, LLAMA_MAX_LAYERS> xielu_eps;

// DSA (deepseek sparse attention)
uint32_t indexer_n_head = 0;
uint32_t indexer_head_size = 0;
uint32_t indexer_top_k = 0;

// qwen3vl deepstack
uint32_t n_deepstack_layers = 0;

Expand Down
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