Model CoverageLarge Language Models (LLMs)

GLM-4

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

TaskText Generation
ArchitectureGlmForCausalLM / Glm4ForCausalLM
Parameters9B – 32B
HF OrgTHUDM

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

ModelHF ID
GLM-4-9B-Chat-HFTHUDM/glm-4-9b-chat-hf
GLM-4-32B-0414THUDM/GLM-4-32B-0414

Example Recipes

RecipeDescription
glm_4_9b_chat_hf_squad.yamlSFT — GLM-4 9B on SQuAD
glm_4_9b_chat_hf_hellaswag_fp8.yamlSFT — 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

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:26.04.00

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.

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