Instructions to use TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8 with Transformers:

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

pipe = pipeline("text-generation", model="TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8", trust_remote_code=True, device_map="auto")
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 Settings

vLLM

How to use TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8

SGLang

How to use TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8 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 "TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8" \
    --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": "TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8",
		"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 "TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8" \
        --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": "TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8 with Docker Model Runner:
```
docker model run hf.co/TMElyralab/DeepSeek-R1-0528-AWQ-W4AFP8
```

我使用sglang运行该模型的时候，会报“quant_method is not None”

by wangliuwei - opened Aug 9, 2025

Discussion

wangliuwei

Aug 9, 2025

sglang版本： v0.4.10.post2

运行命令:
python3 -m sglang.launch_server
--model-path /deepseek-v3/DeepSeek-R1-0528-AWQ-W4AFP8
--speculative-algorithm NEXTN
--speculative-num-steps 2
--speculative-eagle-topk 1
--speculative-num-draft-tokens 8
--served-model-name deepseek-r1-0528
--trust-remote-code
--tp 8
--host 0.0.0.0 --port 30000
--max-prefill-tokens 16384
--max-running-requests 48
--disable-radix-cache
--mem-fraction-static 0.85
--chunked-prefill-size 8192
--schedule-conservativeness 0.01
--cuda-graph-max-bs=160
--quantization awq
--dtype float16
--stream-output

错误信息：
[2025-08-09 14:23:53] Received sigquit from a child process. It usually means the child failed.
[2025-08-09 14:23:54 TP6] Scheduler hit an exception: Traceback (most recent call last):
File "/sgl-workspace/sglang/python/sglang/srt/managers/scheduler.py", line 2534, in run_scheduler_process
scheduler = Scheduler(
File "/sgl-workspace/sglang/python/sglang/srt/managers/scheduler.py", line 313, in init
self.tp_worker = TpWorkerClass(
File "/sgl-workspace/sglang/python/sglang/srt/managers/tp_worker.py", line 84, in init
self.model_runner = ModelRunner(
File "/sgl-workspace/sglang/python/sglang/srt/model_executor/model_runner.py", line 242, in init
self.initialize(min_per_gpu_memory)
File "/sgl-workspace/sglang/python/sglang/srt/model_executor/model_runner.py", line 285, in initialize
self.load_model()
File "/sgl-workspace/sglang/python/sglang/srt/model_executor/model_runner.py", line 643, in load_model
self.model = get_model(
File "/sgl-workspace/sglang/python/sglang/srt/model_loader/init.py", line 22, in get_model
return loader.load_model(
File "/sgl-workspace/sglang/python/sglang/srt/model_loader/loader.py", line 432, in load_model
model = _initialize_model(
File "/sgl-workspace/sglang/python/sglang/srt/model_loader/loader.py", line 174, in _initialize_model
return model_class(
File "/sgl-workspace/sglang/python/sglang/srt/models/deepseek_v2.py", line 2075, in init
self.model = DeepseekV2Model(
File "/sgl-workspace/sglang/python/sglang/srt/models/deepseek_v2.py", line 1990, in init
[
File "/sgl-workspace/sglang/python/sglang/srt/models/deepseek_v2.py", line 1991, in
DeepseekV2DecoderLayer(
File "/sgl-workspace/sglang/python/sglang/srt/models/deepseek_v2.py", line 1792, in init
self.mlp = DeepseekV2MoE(
File "/sgl-workspace/sglang/python/sglang/srt/models/deepseek_v2.py", line 325, in init
self.experts = get_moe_impl_class()(
File "/sgl-workspace/sglang/python/sglang/srt/layers/moe/fused_moe_triton/layer.py", line 161, in init
assert self.quant_method is not None
AssertionError

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