Files
llama.cpp/conversion/olmo.py
2026-08-17 01:54:08 +02:00

76 lines
2.5 KiB
Python

from __future__ import annotations
from typing import Iterable, TYPE_CHECKING
if TYPE_CHECKING:
from torch import Tensor
from .base import MOE_HF_MLP, ModelBase, TextModel, gguf
from .llama import LlamaModel
@ModelBase.register("OlmoForCausalLM")
@ModelBase.register("OLMoForCausalLM")
class OlmoModel(TextModel):
model_arch = gguf.MODEL_ARCH.OLMO
def set_gguf_parameters(self):
super().set_gguf_parameters()
self.gguf_writer.add_layer_norm_eps(1e-5)
clip_qkv = self.hparams.get("clip_qkv")
if clip_qkv is not None:
self.gguf_writer.add_clamp_kqv(clip_qkv)
# Same as super class, but permuting q_proj, k_proj
# Copied from: LlamaModel
def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
n_head = self.hparams["num_attention_heads"]
n_kv_head = self.hparams.get("num_key_value_heads")
if name.endswith("q_proj.weight"):
data_torch = LlamaModel.permute(data_torch, n_head, n_head)
if name.endswith("k_proj.weight"):
data_torch = LlamaModel.permute(data_torch, n_head, n_kv_head)
yield from super().modify_tensors(data_torch, name, bid)
@ModelBase.register("SeedOssForCausalLM")
class SeedOssModel(TextModel):
model_arch = gguf.MODEL_ARCH.SEED_OSS
@ModelBase.register("Olmo2ForCausalLM")
@ModelBase.register("Olmo3ForCausalLM")
class Olmo2Model(TextModel):
model_arch = gguf.MODEL_ARCH.OLMO2
def set_gguf_parameters(self):
super().set_gguf_parameters()
if "sliding_window" in self.hparams:
self.gguf_writer.add_sliding_window(self.hparams["sliding_window"])
sliding_window_pattern = []
if "layer_types" in self.hparams:
sliding_window_pattern = [t == "sliding_attention" for t in self.hparams["layer_types"]]
else:
# Olmo2 does not use sliding window attention.
# Olmo3 defaults to using sliding window for all layers except every 4th.
for i in range(self.hparams["num_hidden_layers"]):
sliding_window_pattern.append((i + 1) % 4 != 0)
self.gguf_writer.add_sliding_window_pattern(sliding_window_pattern)
@ModelBase.register("OlmoeForCausalLM")
class OlmoeModel(TextModel):
model_arch = gguf.MODEL_ARCH.OLMOE
def set_gguf_parameters(self):
super().set_gguf_parameters()
self.gguf_writer.add_layer_norm_rms_eps(1e-5)
moe_experts = [MOE_HF_MLP]