feat: add glm and glm4 multipack and cce (#2546)

* feat: add glm and glm4 multipack

* feat: add glm4 example

* feat: add cce for glm
This commit is contained in:
NanoCode012
2025-04-23 21:27:51 +07:00
committed by GitHub
parent 32e335dd51
commit a6d28d19b1
5 changed files with 129 additions and 0 deletions

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@@ -0,0 +1,62 @@
base_model: THUDM/GLM-4-32B-0414
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
load_in_4bit: true
datasets:
- path: teknium/GPT4-LLM-Cleaned
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0
output_dir: ./outputs/qlora-out
adapter: qlora
lora_model_dir:
sequence_len: 2048
sample_packing: true
eval_sample_packing: true
pad_to_sequence_len: true
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_8bit
lr_scheduler: cosine
learning_rate: 0.0002
bf16: auto
tf32: false
gradient_checkpointing: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 1
saves_per_epoch: 1
weight_decay: 0.0
special_tokens:

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@@ -47,6 +47,8 @@ cut_cross_entropy: true
- qwen2
- cohere
- cohere2
- glm
- glm4
## Citation

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@@ -0,0 +1,57 @@
"""GLM 4 patch. GLM family inherits from Llama."""
from types import MethodType
import transformers
from cut_cross_entropy.transformers.utils import (
PatchOptions,
TransformersModelT,
)
def patch_glm(
maybe_model: TransformersModelT | str | transformers.PretrainedConfig,
patch_options: PatchOptions,
) -> TransformersModelT | None:
# Set the _PATCH_OPTS in the llama patch file
import cut_cross_entropy.transformers.llama as llama_patch
llama_patch._PATCH_OPTS = patch_options # pylint: disable=protected-access
from cut_cross_entropy.transformers.llama import cce_forward
from transformers.models.glm import modeling_glm
if isinstance(maybe_model, transformers.PreTrainedModel):
assert isinstance(
maybe_model, modeling_glm.GlmForCausalLM
), f"Expected a GlmForCausalLM model. Got {type(maybe_model)}."
maybe_model.forward = MethodType(cce_forward, maybe_model)
return maybe_model
modeling_glm.GlmForCausalLM.forward = cce_forward
return None
def patch_glm4(
maybe_model: TransformersModelT | str | transformers.PretrainedConfig,
patch_options: PatchOptions,
) -> TransformersModelT | None:
# Set the _PATCH_OPTS in the llama patch file
import cut_cross_entropy.transformers.llama as llama_patch
llama_patch._PATCH_OPTS = patch_options # pylint: disable=protected-access
from cut_cross_entropy.transformers.llama import cce_forward
from transformers.models.glm4 import modeling_glm4
if isinstance(maybe_model, transformers.PreTrainedModel):
assert isinstance(
maybe_model, modeling_glm4.Glm4ForCausalLM
), f"Expected a Glm4ForCausalLM model. Got {type(maybe_model)}."
maybe_model.forward = MethodType(cce_forward, maybe_model)
return maybe_model
modeling_glm4.Glm4ForCausalLM.forward = cce_forward
return None

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@@ -20,6 +20,10 @@ from axolotl.integrations.cut_cross_entropy.monkeypatch.gemma3 import (
patch_gemma3,
patch_gemma3_text,
)
from axolotl.integrations.cut_cross_entropy.monkeypatch.glm4 import (
patch_glm,
patch_glm4,
)
from axolotl.integrations.cut_cross_entropy.monkeypatch.llama4 import (
patch_llama4,
patch_llama4_text,
@@ -45,6 +49,8 @@ CUT_CROSS_ENTROPY_MODEL_MAPPING = {
"qwen2": patch_qwen2,
"cohere": patch_cohere,
"cohere2": patch_cohere2,
"glm": patch_glm,
"glm4": patch_glm4,
}

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@@ -31,6 +31,8 @@ SUPPORTED_MULTIPACK_MODEL_TYPES = [
"starcoder2",
"deepseek_v2",
"deepseek_v3",
"glm",
"glm4",
]