Instructions to use GadflyII/GLM-4.7-Flash-MXFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use GadflyII/GLM-4.7-Flash-MXFP4 with Transformers:

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

pipe = pipeline("text-generation", model="GadflyII/GLM-4.7-Flash-MXFP4")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("GadflyII/GLM-4.7-Flash-MXFP4")
model = AutoModelForCausalLM.from_pretrained("GadflyII/GLM-4.7-Flash-MXFP4")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use GadflyII/GLM-4.7-Flash-MXFP4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GadflyII/GLM-4.7-Flash-MXFP4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GadflyII/GLM-4.7-Flash-MXFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/GadflyII/GLM-4.7-Flash-MXFP4

SGLang

How to use GadflyII/GLM-4.7-Flash-MXFP4 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 "GadflyII/GLM-4.7-Flash-MXFP4" \
    --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": "GadflyII/GLM-4.7-Flash-MXFP4",
		"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 "GadflyII/GLM-4.7-Flash-MXFP4" \
        --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": "GadflyII/GLM-4.7-Flash-MXFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use GadflyII/GLM-4.7-Flash-MXFP4 with Docker Model Runner:
```
docker model run hf.co/GadflyII/GLM-4.7-Flash-MXFP4
```

can not run

by aliez-ren - opened Jan 26

Discussion

aliez-ren

Jan 26

Dockerfile

FROM vllm/vllm-openai:nightly-4753f3bf69a2b975361afa7c49e8d948047613f6

RUN apt-get update && apt-get install -y git && \
    apt-get clean && rm -rf /var/lib/apt/lists/*

RUN pip install git+https://github.com/huggingface/transformers.git@76732b4e7120808ff989edbd16401f61fa6a0afa

EXPOSE 8000

ENTRYPOINT ["vllm", "serve", "GadflyII/GLM-4.7-Flash-NVFP4", \
    "--tensor-parallel-size", "1", \
    "--max-model-len", "65536", \
    "--trust-remote-code", \
    "--gpu-memory-utilization", "0.90", \
    "--host", "0.0.0.0"]

Log

(EngineCore_DP0 pid=137)   File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/models/glm4_moe_lite.py", line 508, in load_weights
(EngineCore_DP0 pid=137)     weight_loader(param, loaded_weight)
(EngineCore_DP0 pid=137) TypeError: FusedMoE.weight_loader() missing 3 required positional arguments: 'weight_name', 'shard_id', and 'expert_id'

GadflyII

Owner Jan 26

•

edited Jan 26

Is this for the NVFP4 or MXFP4? (your docker file says NVFP4, but you opened this in the MXFP4 page).

Edit:

If you are trying to run this MXFP4 model on blackwell GPU's. You will need to pull my fork listed in the model card. You will also need to make sure you have the release version of transformers 5.0.0 installed.

aliez-ren

Jan 27

sorry, I pasted a wrong dockerfile.
I both tried MXFP4 and NVFP4. NVFP4 works fine.
so it's necessary to use your vllm fork to run MXFP4, right?
I'll try again. my machine stucked when compiling vllm yesterday.

aliez-ren

Jan 27

I see your new comment in model card.
I choose to keep using NVFP4 for speed.
thanks!

aliez-ren changed discussion status to closed Jan 27

GadflyII

Owner Jan 27

@aliez-ren

Pull and build my fork, make sure you have 5.0.0
release transformers installed, NV4FP model got a lot faster ;)

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