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
del gradient_checkpointing_enable()
#11
by chandler88 - opened
- modeling_chatglm.py +0 -4
modeling_chatglm.py
CHANGED
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@@ -797,10 +797,6 @@ class ChatGLMPreTrainedModel(PreTrainedModel):
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position_ids = torch.arange(seq_length, dtype=torch.long, device=device).unsqueeze(0).repeat(batch_size, 1)
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return position_ids
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-
def gradient_checkpointing_enable(self, gradient_checkpointing_kwargs=None):
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if not self.supports_gradient_checkpointing:
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raise ValueError(f"{self.__class__.__name__} does not support gradient checkpointing.")
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class Embedding(torch.nn.Module):
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"""Language model embeddings."""
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position_ids = torch.arange(seq_length, dtype=torch.long, device=device).unsqueeze(0).repeat(batch_size, 1)
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return position_ids
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class Embedding(torch.nn.Module):
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"""Language model embeddings."""
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