Files
llama.cpp/conversion/smallthinker.py
T

38 lines
1.7 KiB
Python

from __future__ import annotations
from .base import MOE_BLOCK_SPARSE, ModelBase, TextModel, gguf, logger
@ModelBase.register("SmallThinkerForCausalLM")
class SmallThinkerModel(TextModel):
model_arch = gguf.MODEL_ARCH.SMALLTHINKER
def set_gguf_parameters(self):
super().set_gguf_parameters()
if (n_experts := self.hparams.get("moe_num_primary_experts")) is not None:
self.gguf_writer.add_expert_count(n_experts)
if (n_experts_used := self.hparams.get("moe_num_active_primary_experts")) is not None:
self.gguf_writer.add_expert_used_count(n_experts_used)
if (moe_intermediate_size := self.hparams.get("moe_ffn_hidden_size")) is not None:
self.gguf_writer.add_expert_feed_forward_length(moe_intermediate_size)
self.gguf_writer.add_feed_forward_length(moe_intermediate_size)
logger.info(f"gguf: expert feed forward length = {moe_intermediate_size}")
if (self.hparams.get('moe_primary_router_apply_softmax')):
self.gguf_writer.add_expert_gating_func(gguf.ExpertGatingFuncType.SOFTMAX)
else:
self.gguf_writer.add_expert_gating_func(gguf.ExpertGatingFuncType.SIGMOID)
sliding_window_layout = self.hparams.get("sliding_window_layout")
if sliding_window_layout:
for i in sliding_window_layout:
if i != 0:
sliding_window = self.hparams.get("sliding_window_size")
if sliding_window:
self.gguf_writer.add_sliding_window(sliding_window)
break
moe_experts = [MOE_BLOCK_SPARSE._replace(
weights=("down", "gate", "up"),
n_expert=("moe_num_primary_experts", "num_local_experts", "num_experts"),
)]