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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/tensor_mapping.py
+9
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@@ -359,6 +359,7 @@ class TensorNameMap:
MODEL_TENSOR.ATTN_GATE: (
"model.layers.{bid}.self_attn.gate_proj", # afmoe
"model.layers.{bid}.self_attn.g_proj", # step3.5 head-wise attention gate
),
# Feed-forward norm
@@ -423,6 +424,7 @@ class TensorNameMap:
"model.layers.{bid}.mlp.router.gate", # afmoe
"layers.{bid}.gate", # mistral-large
"backbone.layers.{bid}.mixer.gate", # nemotron-h-moe
"model.layers.{bid}.moe.gate", # step3.5
),
MODEL_TENSOR.FFN_GATE_INP_SHEXP: (
@@ -439,6 +441,7 @@ class TensorNameMap:
"backbone.layers.{bid}.mixer.gate.e_score_correction", # nemotron-h-moe
"model.layers.{bid}.mlp.e_score_correction", # exaone-moe
"model.layers.{bid}.block_sparse_moe.gate.e_score_correction", # kimi
"model.layers.{bid}.moe.router_bias", # step3.5 expert selection bias
),
# Feed-forward up
@@ -493,6 +496,7 @@ class TensorNameMap:
"model.layers.{bid}.feed_forward.experts.up_proj", # llama4
"encoder.layers.{bid}.mlp.experts.mlp.w1", # nomic-bert-moe
"model.layers.{bid}.block_sparse_moe.experts.up", # smallthinker
"model.layers.{bid}.moe.up_proj", # step3.5
),
MODEL_TENSOR.FFN_UP_SHEXP: (
@@ -504,6 +508,7 @@ class TensorNameMap:
"layers.{bid}.shared_experts.w3", # mistral-large
"backbone.layers.{bid}.mixer.shared_experts.up_proj", # nemotron-h-moe
"model.layers.{bid}.block_sparse_moe.shared_experts.up_proj", # kimi
"model.layers.{bid}.share_expert.up_proj", # step3.5
),
MODEL_TENSOR.FFN_UP_CHEXP: (
@@ -543,6 +548,7 @@ class TensorNameMap:
"model.layers.{bid}.block_sparse_moe.experts.w1", # phimoe (merged)
"model.layers.{bid}.feed_forward.experts.gate_proj", # llama4
"model.layers.{bid}.block_sparse_moe.experts.gate", # smallthinker
"model.layers.{bid}.moe.gate_proj", # step3.5
),
MODEL_TENSOR.FFN_GATE_SHEXP: (
@@ -552,6 +558,7 @@ class TensorNameMap:
"model.layers.{bid}.mlp.shared_mlp.gate_proj", # hunyuan
"layers.{bid}.shared_experts.w1", # mistral-large
"model.layers.{bid}.block_sparse_moe.shared_experts.gate_proj", # kimi
"model.layers.{bid}.share_expert.gate_proj", # step3.5
),
MODEL_TENSOR.FFN_GATE_CHEXP: (
@@ -606,6 +613,7 @@ class TensorNameMap:
"model.layers.{bid}.feed_forward.experts.down_proj", # llama4
"encoder.layers.{bid}.mlp.experts.mlp.w2", # nomic-bert-moe
"model.layers.{bid}.block_sparse_moe.experts.down", # smallthinker
"model.layers.{bid}.moe.down_proj", # step3.5
),
MODEL_TENSOR.FFN_DOWN_SHEXP: (
@@ -617,6 +625,7 @@ class TensorNameMap:
"layers.{bid}.shared_experts.w2", # mistral-large
"backbone.layers.{bid}.mixer.shared_experts.down_proj", # nemotron-h-moe
"model.layers.{bid}.block_sparse_moe.shared_experts.down_proj", # kimi
"model.layers.{bid}.share_expert.down_proj", # step3.5
),
MODEL_TENSOR.FFN_DOWN_CHEXP: (