Instructions to use zai-org/glm-4-9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zai-org/glm-4-9b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zai-org/glm-4-9b", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zai-org/glm-4-9b", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use zai-org/glm-4-9b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zai-org/glm-4-9b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zai-org/glm-4-9b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/zai-org/glm-4-9b
- SGLang
How to use zai-org/glm-4-9b 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-4-9b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zai-org/glm-4-9b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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-4-9b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zai-org/glm-4-9b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use zai-org/glm-4-9b with Docker Model Runner:
docker model run hf.co/zai-org/glm-4-9b
AttributeError: module 'transformers_modules.GLM-4-9B.tokenization_chatglm' has no attribute 'ChatGLM4Tokenizer'
transformers==4.40.0
modelscope==1.14
accelerate==0.30.1
deepspeed== 0.14.4
sentencepiece==0.1.99
用transformers库吧,modelscope用不到呀
然后你这个是什么时候报错的
我在用swift微调的时候,会在模型加载过程中遇到相关报错
File "/home/jeeves/.local/lib/python3.10/site-packages/swift/utils/run_utils.py", line 27, in x_main
result = llm_x(args, **kwargs)
File "/local/apps/zai-model/model_llm_sft/nlp_v2/llm_sft.py", line 97, in llm_sft
model, tokenizer = get_model_tokenizer(
File "/home/jeeves/.local/lib/python3.10/site-packages/swift/llm/utils/model.py", line 4843, in get_model_tokenizer
model, tokenizer = get_function(model_dir, torch_dtype, model_kwargs, load_model, **kwargs)
File "/home/jeeves/.local/lib/python3.10/site-packages/swift/llm/utils/model.py", line 1474, in get_model_tokenizer_chatglm
tokenizer_cls = get_class_from_dynamic_module(class_ref, model_dir)
File "/home/jeeves/.local/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 501, in get_class_from_dynamic_module
return get_class_in_module(class_name, final_module)
File "/home/jeeves/.local/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 202, in get_class_in_module
return getattr(module, class_name)
AttributeError: module 'transformers_modules.GLM-4-9B.tokenization_chatglm' has no attribute 'ChatGLM4Tokenizer'
这种情况是偶发出现的,不确定是什么原因导致的