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
```

llama.cpp - Quantize error: KeyError: '<|user|>'

by ayyylol - opened Aug 13, 2024

Discussion

ayyylol

Aug 13, 2024

Hi!,

Thank you for this model!

I'm trying to quantize it using llama.cpp but I'm getting this error:

INFO:hf-to-gguf:Set model parameters
INFO:hf-to-gguf:Set model tokenizer
Traceback (most recent call last):
  File "/home/llama.cpp/convert_hf_to_gguf.py", line 3953, in <module>
    main()
  File "/home/llama.cpp/convert_hf_to_gguf.py", line 3947, in main
    model_instance.write()
  File "/home/llama.cpp/convert_hf_to_gguf.py", line 388, in write
    self.prepare_metadata(vocab_only=False)
  File "/home/llama.cpp/convert_hf_to_gguf.py", line 381, in prepare_metadata
    self.set_vocab()
  File "/home/llama.cpp/convert_hf_to_gguf.py", line 3704, in set_vocab
    special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"])
                                            ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^
KeyError: '<|user|>'

On line 3702 - 3704 of convert_hf_to_gguf.py it says:

# only add special tokens when they were not already loaded from config.json
special_vocab._set_special_token("eos", tokenizer.get_added_vocab()["<|endoftext|>"])
special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"])

If I delete line 3704 it works, but I think that maybe now the EOT is missing?
Should this be fixed?

Thank you!