Instructions to use zai-org/GLM-4-32B-0414 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zai-org/GLM-4-32B-0414 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="zai-org/GLM-4-32B-0414")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("zai-org/GLM-4-32B-0414")
model = AutoModelForCausalLM.from_pretrained("zai-org/GLM-4-32B-0414")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
HuggingChat
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use zai-org/GLM-4-32B-0414 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zai-org/GLM-4-32B-0414"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/GLM-4-32B-0414",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zai-org/GLM-4-32B-0414

SGLang

How to use zai-org/GLM-4-32B-0414 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "zai-org/GLM-4-32B-0414" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/GLM-4-32B-0414",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "zai-org/GLM-4-32B-0414" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/GLM-4-32B-0414",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use zai-org/GLM-4-32B-0414 with Docker Model Runner:
```
docker model run hf.co/zai-org/GLM-4-32B-0414
```

vllm为什么不管问啥，模型回复的内容都是一堆！号呀，全是！！！！！！！！！！！！！！！！

#18

by chaochaoli - opened Jun 3, 2025

Discussion

chaochaoli

Jun 3, 2025

我在v100上，只能用float16启动。
用float32可以正常输出，但是需要占用8张卡，有点费资源。

chaochaoli

Jun 3, 2025

{
"id": "chatcmpl-35d9b03dec7d42079ea18490a820cd9d",
"object": "chat.completion",
"created": 1748922394,
"model": "glm4-32b-0414",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"reasoning_content": null,
"content": "!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!",
"tool_calls": []
},
"logprobs": null,
"finish_reason": "length",
"stop_reason": null
}
],
"usage": {
"prompt_tokens": 59,
"total_tokens": 149,
"completion_tokens": 90,
"prompt_tokens_details": null
},
"prompt_logprobs": null
}

chaochaoli

Jun 23, 2025

精度问题

chaochaoli changed discussion status to closed Jun 23, 2025

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vllm为什么 不管问啥，模型回复的内容都是一 堆！号呀，全是！！！！！！！！！！！！！！！！

vllm为什么不管问啥，模型回复的内容都是一堆！号呀，全是！！！！！！！！！！！！！！！！