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llama.cpp
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new_name not needed

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Sigbjørn Skjæret 2026-03-21 15:44:31 +01:00 committed by GitHub
parent fa0b3144f6
commit ca5a877ec3
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1 changed files with 3 additions and 5 deletions
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8
convert_hf_to_gguf.py
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@ -605,7 +605,7 @@ class ModelBase:
def _nvfp4_scale2_is_trivial(scale2: Tensor) -> bool:
return scale2.numel() <= 1 and abs(float(scale2.float().sum()) - 1.0) < 1e-6
def _repack_nvfp4(self, name: str, weight: Tensor, scale: Tensor, scale2: Tensor) -> str:
def _repack_nvfp4(self, name: str, weight: Tensor, scale: Tensor, scale2: Tensor):
if "language_model." in name:
name = name.replace("language_model.", "")
@ -622,8 +622,6 @@ class ModelBase:
logger.info(f" + {scale_name} (per-tensor NVFP4 scale2, shape [{scale2_f32.size}])")
self.gguf_writer.add_tensor(scale_name, scale2_f32)
return new_name
def _generate_nvfp4_tensors(self):
# Per-layer expert merging to avoid holding all experts in memory
expert_blocks: dict[tuple[int, str], list[tuple[int, np.ndarray]]] = {}
@ -5073,9 +5071,9 @@ class _LinearAttentionVReorderBase(Qwen3NextModel):
return weight, scale
def _repack_nvfp4(self, name: str, weight: Tensor, scale: Tensor, scale2: Tensor) -> str:
def _repack_nvfp4(self, name: str, weight: Tensor, scale: Tensor, scale2: Tensor):
weight, scale = self._transform_nvfp4_weight(name, weight, scale)
return super()._repack_nvfp4(name, weight, scale, scale2)
super()._repack_nvfp4(name, weight, scale, scale2)
def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
num_k_heads = self.hparams.get("linear_num_key_heads", 0)