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model : support Step3.5-Flash (#19283)

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* Support Step3.5-Flash

* fix: norm.weight + 1 (HF zero_centered=true)

* step35: simplify GGUF conversion + drop redundant rope KVs

* Address review feedback

* rename limits -> clamp

* Apply suggestions from code review

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Apply suggestion from @CISC

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* rename swiglu limits -> swiglu clamp in LLM_KV

* avoid CI fail

* Apply suggestions from code review

* Apply suggestions from code review

* disabled KV shifting for LLM_ARCH_STEP35

* Apply suggestions from code review

* mistakenly removed cmath

* add model size && apply missed suggestion

* assert partial_rotary_factors

* fix CI errors:

* load freq_base_swa

---------

Co-authored-by: lvyichen <lvyichen@stepfun.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
This commit is contained in:
forforever73
2026-02-06 21:06:14 +01:00
committed by GitHub
co-authored by Sigbjørn Skjæret lvyichen
parent 3228e77287
commit b83111815e
15 changed files with 576 additions and 38 deletions
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gguf-py/gguf/constants.py
+50 -20
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@@ -146,6 +146,8 @@ class Keys:
ALTUP_ACTIVE_IDX = "{arch}.altup.active_idx"
ALTUP_NUM_INPUTS = "{arch}.altup.num_inputs"
EMBD_LENGTH_PER_LAYER_INP = "{arch}.embedding_length_per_layer_input"
SWIGLU_CLAMP_EXP = "{arch}.swiglu_clamp_exp"
SWIGLU_CLAMP_SHEXP = "{arch}.swiglu_clamp_shexp"
DENSE_FEAT_IN_SIZE = "{arch}.{dense}_feat_in"
DENSE_FEAT_OUT_SIZE = "{arch}.{dense}_feat_out"
@@ -179,20 +181,20 @@ class Keys:
TEMPERATURE_SCALE = "{arch}.attention.temperature_scale"
class Rope:
DIMENSION_COUNT = "{arch}.rope.dimension_count"
DIMENSION_SECTIONS = "{arch}.rope.dimension_sections"
FREQ_BASE = "{arch}.rope.freq_base"
FREQ_BASE_SWA = "{arch}.rope.freq_base_swa"
SCALING_TYPE = "{arch}.rope.scaling.type"
SCALING_FACTOR = "{arch}.rope.scaling.factor"
SCALING_ATTN_FACTOR = "{arch}.rope.scaling.attn_factor"
SCALING_ORIG_CTX_LEN = "{arch}.rope.scaling.original_context_length"
SCALING_FINETUNED = "{arch}.rope.scaling.finetuned"
SCALING_YARN_LOG_MUL = "{arch}.rope.scaling.yarn_log_multiplier"
SCALING_YARN_EXT_FACTOR = "{arch}.rope.scaling.yarn_ext_factor"
SCALING_YARN_ATTN_FACTOR = "{arch}.rope.scaling.yarn_attn_factor"
SCALING_YARN_BETA_FAST = "{arch}.rope.scaling.yarn_beta_fast"
SCALING_YARN_BETA_SLOW = "{arch}.rope.scaling.yarn_beta_slow"
DIMENSION_COUNT = "{arch}.rope.dimension_count"
DIMENSION_SECTIONS = "{arch}.rope.dimension_sections"
FREQ_BASE = "{arch}.rope.freq_base"
FREQ_BASE_SWA = "{arch}.rope.freq_base_swa"
SCALING_TYPE = "{arch}.rope.scaling.type"
SCALING_FACTOR = "{arch}.rope.scaling.factor"
SCALING_ATTN_FACTOR = "{arch}.rope.scaling.attn_factor"
SCALING_ORIG_CTX_LEN = "{arch}.rope.scaling.original_context_length"
SCALING_FINETUNED = "{arch}.rope.scaling.finetuned"
SCALING_YARN_LOG_MUL = "{arch}.rope.scaling.yarn_log_multiplier"
SCALING_YARN_EXT_FACTOR = "{arch}.rope.scaling.yarn_ext_factor"
SCALING_YARN_ATTN_FACTOR = "{arch}.rope.scaling.yarn_attn_factor"
SCALING_YARN_BETA_FAST = "{arch}.rope.scaling.yarn_beta_fast"
SCALING_YARN_BETA_SLOW = "{arch}.rope.scaling.yarn_beta_slow"
class Split:
LLM_KV_SPLIT_NO = "split.no"
@@ -462,6 +464,7 @@ class MODEL_ARCH(IntEnum):
PANGU_EMBED = auto()
MISTRAL3 = auto()
MIMO2 = auto()
STEP35 = auto()
LLAMA_EMBED = auto()
MAINCODER = auto()
KIMI_LINEAR = auto()
@@ -892,6 +895,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
MODEL_ARCH.PANGU_EMBED: "pangu-embedded",
MODEL_ARCH.MISTRAL3: "mistral3",
MODEL_ARCH.MIMO2: "mimo2",
MODEL_ARCH.STEP35: "step35",
MODEL_ARCH.LLAMA_EMBED: "llama-embed",
MODEL_ARCH.MAINCODER: "maincoder",
MODEL_ARCH.KIMI_LINEAR: "kimi-linear",
@@ -3364,6 +3368,32 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
MODEL_TENSOR.FFN_UP_EXP,
MODEL_TENSOR.FFN_EXP_PROBS_B,
],
MODEL_ARCH.STEP35: [
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_NORM,
MODEL_TENSOR.ATTN_K,
MODEL_TENSOR.ATTN_K_NORM,
MODEL_TENSOR.ATTN_V,
MODEL_TENSOR.ATTN_GATE,
MODEL_TENSOR.ATTN_OUT,
MODEL_TENSOR.FFN_NORM,
MODEL_TENSOR.FFN_GATE,
MODEL_TENSOR.FFN_DOWN,
MODEL_TENSOR.FFN_UP,
MODEL_TENSOR.FFN_GATE_INP,
MODEL_TENSOR.FFN_GATE_EXP,
MODEL_TENSOR.FFN_DOWN_EXP,
MODEL_TENSOR.FFN_UP_EXP,
MODEL_TENSOR.FFN_UP_SHEXP,
MODEL_TENSOR.FFN_GATE_SHEXP,
MODEL_TENSOR.FFN_DOWN_SHEXP,
MODEL_TENSOR.FFN_EXP_PROBS_B,
],
MODEL_ARCH.LLAMA_EMBED: [
MODEL_TENSOR.TOKEN_EMBD,
MODEL_TENSOR.OUTPUT_NORM,
@@ -3753,12 +3783,12 @@ KEY_ATTENTION_LAYERNORM_EPS = Keys.Attention.LAYERNORM_EPS
KEY_ATTENTION_LAYERNORM_RMS_EPS = Keys.Attention.LAYERNORM_RMS_EPS
# RoPE
KEY_ROPE_DIMENSION_COUNT = Keys.Rope.DIMENSION_COUNT
KEY_ROPE_FREQ_BASE = Keys.Rope.FREQ_BASE
KEY_ROPE_SCALING_TYPE = Keys.Rope.SCALING_TYPE
KEY_ROPE_SCALING_FACTOR = Keys.Rope.SCALING_FACTOR
KEY_ROPE_SCALING_ORIG_CTX_LEN = Keys.Rope.SCALING_ORIG_CTX_LEN
KEY_ROPE_SCALING_FINETUNED = Keys.Rope.SCALING_FINETUNED
KEY_ROPE_DIMENSION_COUNT = Keys.Rope.DIMENSION_COUNT
KEY_ROPE_FREQ_BASE = Keys.Rope.FREQ_BASE
KEY_ROPE_SCALING_TYPE = Keys.Rope.SCALING_TYPE
KEY_ROPE_SCALING_FACTOR = Keys.Rope.SCALING_FACTOR
KEY_ROPE_SCALING_ORIG_CTX_LEN = Keys.Rope.SCALING_ORIG_CTX_LEN
KEY_ROPE_SCALING_FINETUNED = Keys.Rope.SCALING_FINETUNED
# SSM
KEY_SSM_CONV_KERNEL = Keys.SSM.CONV_KERNEL