Instructions to use zai-org/GLM-4.7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zai-org/GLM-4.7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zai-org/GLM-4.7") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zai-org/GLM-4.7") model = AutoModelForCausalLM.from_pretrained("zai-org/GLM-4.7") 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 Settings
- vLLM
How to use zai-org/GLM-4.7 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zai-org/GLM-4.7" # 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-4.7", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/zai-org/GLM-4.7
- SGLang
How to use zai-org/GLM-4.7 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-4.7" \ --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-4.7", "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-4.7" \ --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-4.7", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use zai-org/GLM-4.7 with Docker Model Runner:
docker model run hf.co/zai-org/GLM-4.7
When running GLM-4.7 with sglang-0.5.6 to process a /v1/chat/completions request, it encounters a BadRequestError
#30
by tuo02 - opened
I am running GLM-4.7 on 32 RTX 5090 cards, and this is my launch command :
python3 -m sglang.launch_server \
--model-path /mnt/data/models/GLM-4.7 \
--tp-size 32 \
--trust-remote-code \
--dist-init-addr $MASTER_ADDR:$MASTER_PORT \
--nnodes $WORLD_SIZE \
--node-rank $RANK \
--tool-call-parser glm \
--reasoning-parser glm45 \
--speculative-algorithm EAGLE \
--speculative-num-steps 3 \
--speculative-eagle-topk 1 \
--speculative-num-draft-tokens 4 \
--mem-fraction-static 0.7 \
--context-length 202752 \
--served-model-name zai-org/GLM-4.7 \
--model-loader-extra-config='{"enable_multithread_load": "true","num_threads": 64}' \
--enable-metrics
and the request is :
curl localhost:30000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "zai-org/GLM-4.7",
"messages": [
{
"role": "user",
"content": "Hello"
}
],
"temperature": 0.7,
"max_tokens": 100
}'
while the response is:
{"object":"error","message":"input_ids should be a list of lists for batch processing.","type":"BadRequestError","param":null,"code":400}
Is there something wrong ?
try using transformers with 5.0.0rc1? or 4.57.1, one of this work
try using transformers with 5.0.0rc1? or 4.57.1, one of this work
4.57.1 is ok.