Instructions to use UCloud-org/GLM-5.2-FP8-DFlash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use UCloud-org/GLM-5.2-FP8-DFlash with Transformers:

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

pipe = pipeline("text-generation", model="UCloud-org/GLM-5.2-FP8-DFlash", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("UCloud-org/GLM-5.2-FP8-DFlash", trust_remote_code=True)
model = AutoModel.from_pretrained("UCloud-org/GLM-5.2-FP8-DFlash", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use UCloud-org/GLM-5.2-FP8-DFlash with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "UCloud-org/GLM-5.2-FP8-DFlash"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "UCloud-org/GLM-5.2-FP8-DFlash",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/UCloud-org/GLM-5.2-FP8-DFlash

SGLang

How to use UCloud-org/GLM-5.2-FP8-DFlash 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 "UCloud-org/GLM-5.2-FP8-DFlash" \
    --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": "UCloud-org/GLM-5.2-FP8-DFlash",
		"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 "UCloud-org/GLM-5.2-FP8-DFlash" \
        --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": "UCloud-org/GLM-5.2-FP8-DFlash",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use UCloud-org/GLM-5.2-FP8-DFlash with Docker Model Runner:
```
docker model run hf.co/UCloud-org/GLM-5.2-FP8-DFlash
```

GLM-5.2-FP8-DFlash

File size: 761 Bytes

3b71a39

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  "backend": "tokenizers",
  "clean_up_tokenization_spaces": false,
  "do_lower_case": false,
  "eos_token": "<|endoftext|>",
  "extra_special_tokens": [
    "<|endoftext|>",
    "[MASK]",
    "[gMASK]",
    "[sMASK]",
    "<sop>",
    "<eop>",
    "<|system|>",
    "<|user|>",
    "<|assistant|>",
    "<|observation|>",
    "<|begin_of_image|>",
    "<|end_of_image|>",
    "<|begin_of_video|>",
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    "<|begin_of_audio|>",
    "<|end_of_audio|>",
    "<|begin_of_transcription|>",
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  ],
  "is_local": true,
  "model_max_length": 1048576,
  "model_specific_special_tokens": {},
  "pad_token": "<|endoftext|>",
  "padding_side": "left",
  "remove_space": false,
  "tokenizer_class": "TokenizersBackend"
}