Skip to content

UPSTREAM PR #19170: Add Kimi-K2.5 support #1068

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
loci-dev wants to merge 2 commits into
base: main
Choose a base branch
from
Open

UPSTREAM PR #19170: Add Kimi-K2.5 support #1068

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
f0143d8
Move dequant_model to after the text_config merge
AesSedai Jan 29, 2026
a23624c
Fix a couple of oversights
AesSedai Jan 29, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
39 changes: 28 additions & 11 deletions convert_hf_to_gguf.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -160,8 +160,6 @@ def __init__(self, dir_model: Path, ftype: gguf.LlamaFileType, fname_out: Path,
self.ftype = gguf.LlamaFileType.MOSTLY_F16
logger.info("heuristics unable to detect tensor dtype, defaulting to --outtype f16")

self.dequant_model()

# Configure GGUF Writer
self.gguf_writer = gguf.GGUFWriter(path=None, arch=gguf.MODEL_ARCH_NAMES[self.model_arch], endianess=self.endianess, use_temp_file=self.use_temp_file,
split_max_tensors=split_max_tensors, split_max_size=split_max_size, dry_run=dry_run, small_first_shard=small_first_shard)
Expand Down Expand Up @@ -527,6 +525,8 @@ def generate_extra_tensors(self) -> Iterable[tuple[str, Tensor]]:
return ()

def prepare_tensors(self):
self.dequant_model()

# Handle empty tensor_map for models with block_count=0 (like MobileNetV5)
if self.tensor_map.mapping:
max_name_len = max(len(s) for _, s in self.tensor_map.mapping.values()) + len(".weight,")
Expand Down Expand Up @@ -1808,7 +1808,7 @@ class MmprojModel(ModelBase):
preprocessor_config: dict[str, Any]
global_config: dict[str, Any]

n_block_keys = ["n_layers", "num_hidden_layers", "n_layer", "num_layers", "depth", "encoder_layers"]
n_block_keys = ["n_layers", "num_hidden_layers", "n_layer", "num_layers", "depth", "encoder_layers", "vt_num_hidden_layers"]

has_vision_encoder: bool = True # by default
has_audio_encoder: bool = False
Expand Down Expand Up @@ -1863,7 +1863,15 @@ def __init__(self, *args, **kwargs):
preprocessor_config_path = self.dir_model / "preprocessor_config.json"
if preprocessor_config_path.is_file():
with open(preprocessor_config_path, "r", encoding="utf-8") as f:
self.preprocessor_config = json.load(f)
cfg = json.load(f)
# move media_proc_cfg to root level for compat
if "media_proc_cfg" in cfg:
cfg = {
**cfg,
**cfg["media_proc_cfg"],
}
# merge configs
self.preprocessor_config = {**self.preprocessor_config, **cfg}

# prefer processor_config.json if possible
processor_config_path = self.dir_model / "processor_config.json"
Expand Down Expand Up @@ -1912,10 +1920,10 @@ def set_gguf_parameters(self):
self.image_size = self.find_vparam(["image_size"])
self.gguf_writer.add_vision_image_size(self.image_size)
self.gguf_writer.add_vision_patch_size(self.find_vparam(["patch_size"]))
self.gguf_writer.add_vision_embedding_length(self.find_vparam(["hidden_size"]))
self.gguf_writer.add_vision_feed_forward_length(self.find_vparam(["intermediate_size"]))
self.gguf_writer.add_vision_embedding_length(self.find_vparam(["hidden_size", "vt_hidden_size"]))
self.gguf_writer.add_vision_feed_forward_length(self.find_vparam(["intermediate_size", "vt_intermediate_size"]))
self.gguf_writer.add_vision_block_count(self.find_vparam(self.n_block_keys))
self.gguf_writer.add_vision_head_count(self.find_vparam(["num_attention_heads", "num_heads"]))
self.gguf_writer.add_vision_head_count(self.find_vparam(["num_attention_heads", "num_heads", "vt_num_attention_heads"]))

# preprocessor config
image_mean = _MISTRAL_COMMON_DATASET_MEAN if self.is_mistral_format else self.preprocessor_config["image_mean"]
Expand Down Expand Up @@ -7360,6 +7368,7 @@ def prepare_tensors(self):
"DeepseekV2ForCausalLM",
"DeepseekV3ForCausalLM",
"KimiVLForConditionalGeneration",
"KimiK25ForConditionalGeneration",
"YoutuForCausalLM",
"YoutuVLForConditionalGeneration",
)
Expand Down Expand Up @@ -7478,8 +7487,8 @@ def set_gguf_parameters(self):
_experts: list[dict[str, Tensor]] | None = None

def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
# skip vision tensors and remove "language_model." for Kimi-VL
if "vision_tower" in name or "multi_modal_projector" in name:
# skip vision tensors and remove "language_model." for Kimi-VL and Kimi-K2.5
if "vision_tower" in name or "multi_modal_projector" in name or "mm_projector" in name:
return
if name.startswith("siglip2.") or name.startswith("merger."):
return
Expand Down Expand Up @@ -10675,7 +10684,7 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None):
yield from super().modify_tensors(data_torch, name, bid)


@ModelBase.register("KimiVLForConditionalGeneration")
@ModelBase.register("KimiVLForConditionalGeneration", "KimiK25ForConditionalGeneration")
class KimiVLModel(MmprojModel):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
Expand All @@ -10692,9 +10701,17 @@ def set_gguf_parameters(self):
self.gguf_writer.add_vision_attention_layernorm_eps(self.hparams_vision.get("layer_norm_eps", 1e-5))

def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
is_vision_tensor = "vision_tower" in name or "multi_modal_projector" in name
is_vision_tensor = "vision_tower" in name or "multi_modal_projector" in name or "mm_projector" in name

if is_vision_tensor:
# update names:
# "mm_projector.proj.0" -> "mm_projector.proj.linear_1.",
# "mm_projector.proj.2" -> "mm_projector.proj.linear_2.",
if "proj.0." in name:
name = name.replace(".0.", ".linear_1.")
if "proj.2." in name:
name = name.replace(".2.", ".linear_2.")

if "pos_emb.weight" in name:
data_torch = data_torch.view(data_torch.shape[0] * data_torch.shape[1], data_torch.shape[2])

Expand Down
2 changes: 2 additions & 0 deletions gguf-py/gguf/tensor_mapping.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1255,6 +1255,7 @@ class TensorNameMap:

MODEL_TENSOR.V_MMPROJ: (
"multi_modal_projector.linear_{bid}",
"mm_projector.proj.linear_{bid}", # Kimi-K2.5
"visual.merger.mlp.{bid}", # qwen2vl
"merger.mlp.{bid}",
),
Expand Down Expand Up @@ -1490,6 +1491,7 @@ class TensorNameMap:
"multi_modal_projector.norm",
"multi_modal_projector.layer_norm",
"multi_modal_projector.pre_norm",
"mm_projector.pre_norm", # Kimi-K2.5
"pre_mm_projector_norm",
"model.vision.linear_proj.norm1", # cogvlm
"merger.ln_q",
Expand Down