Instructions to use zai-org/LongWriter-glm4-9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zai-org/LongWriter-glm4-9b with Transformers:

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

pipe = pipeline("text-generation", model="zai-org/LongWriter-glm4-9b", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("zai-org/LongWriter-glm4-9b", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use zai-org/LongWriter-glm4-9b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zai-org/LongWriter-glm4-9b"
# 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/LongWriter-glm4-9b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zai-org/LongWriter-glm4-9b

SGLang

How to use zai-org/LongWriter-glm4-9b 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/LongWriter-glm4-9b" \
    --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/LongWriter-glm4-9b",
		"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/LongWriter-glm4-9b" \
        --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/LongWriter-glm4-9b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use zai-org/LongWriter-glm4-9b with Docker Model Runner:
```
docker model run hf.co/zai-org/LongWriter-glm4-9b
```

ayyylol commited on Oct 2, 2024

Commit

2e7f691

verified ·

1 Parent(s): 9896eb9

Fix TypeError in _pad method by adding missing padding_side field (#9)

Browse files

- Fix TypeError in _pad method by adding missing padding_side field (778b5712634889f5123d6c463ca383bc6dd5c621)

Co-authored-by: Ayyylol <ayyylol@users.noreply.huggingface.co>

Files changed (1) hide show

tokenization_chatglm.py +1 -0

tokenization_chatglm.py CHANGED Viewed

@@ -207,6 +207,7 @@ class ChatGLM4Tokenizer(PreTrainedTokenizer):
             padding_strategy: PaddingStrategy = PaddingStrategy.DO_NOT_PAD,
             pad_to_multiple_of: Optional[int] = None,
             return_attention_mask: Optional[bool] = None,
     ) -> dict:
         """
         Pad encoded inputs (on left/right and up to predefined length or max length in the batch)

             padding_strategy: PaddingStrategy = PaddingStrategy.DO_NOT_PAD,
             pad_to_multiple_of: Optional[int] = None,
             return_attention_mask: Optional[bool] = None,
+            padding_side: Optional[str] = None,
     ) -> dict:
         """
         Pad encoded inputs (on left/right and up to predefined length or max length in the batch)