GLM-4#

GLM-4 is Tsinghua University (THUDM)’s fourth-generation General Language Model, featuring strong multilingual capabilities and tool-use support.

Task

Text Generation

Architecture

GlmForCausalLM / Glm4ForCausalLM

Parameters

9B – 32B

HF Org

THUDM

Available Models#

  • GLM-4-9B-Chat-HF (GlmForCausalLM): 9B

  • GLM-4-32B-0414 (Glm4ForCausalLM): 32B

Architectures#

  • GlmForCausalLM — GLM-4 series

  • Glm4ForCausalLM — GLM-4-0414 series

Example HF Models#

Model

HF ID

GLM-4-9B-Chat-HF

THUDM/glm-4-9b-chat-hf

GLM-4-32B-0414

THUDM/GLM-4-32B-0414

Example Recipes#

Recipe

Description

glm_4_9b_chat_hf_squad.yaml

SFT — GLM-4 9B on SQuAD

glm_4_9b_chat_hf_hellaswag_fp8.yaml

SFT — GLM-4 9B on HellaSwag with FP8

Try with NeMo AutoModel#

1. Install (full instructions):

pip install nemo-automodel

2. Clone the repo to get the example recipes:

git clone https://github.com/NVIDIA-NeMo/Automodel.git
cd Automodel

3. Run the recipe from inside the repo:

automodel --nproc-per-node=8 examples/llm_finetune/glm/glm_4_9b_chat_hf_squad.yaml
Run with Docker

1. Pull the container and mount a checkpoint directory:

docker run --gpus all -it --rm \
  --shm-size=8g \
  -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
  nvcr.io/nvidia/nemo-automodel:26.02.00

2. Navigate to the AutoModel directory (where the recipes are):

cd /opt/Automodel

3. Run the recipe:

automodel --nproc-per-node=8 examples/llm_finetune/glm/glm_4_9b_chat_hf_squad.yaml

See the Installation Guide and LLM Fine-Tuning Guide.

Fine-Tuning#

See the LLM Fine-Tuning Guide.

Hugging Face Model Cards#