Instructions to use tiny-random/deepseek-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tiny-random/deepseek-v4 with Transformers:

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

pipe = pipeline("text-generation", model="tiny-random/deepseek-v4")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tiny-random/deepseek-v4")
model = AutoModelForCausalLM.from_pretrained("tiny-random/deepseek-v4", 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 tiny-random/deepseek-v4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tiny-random/deepseek-v4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiny-random/deepseek-v4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tiny-random/deepseek-v4

SGLang

How to use tiny-random/deepseek-v4 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 "tiny-random/deepseek-v4" \
    --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": "tiny-random/deepseek-v4",
		"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 "tiny-random/deepseek-v4" \
        --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": "tiny-random/deepseek-v4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use tiny-random/deepseek-v4 with Docker Model Runner:
```
docker model run hf.co/tiny-random/deepseek-v4
```

yujiepan commited on 9 days ago

Commit

bf6d9d5

verified ·

1 Parent(s): 30ad698

Upload folder using huggingface_hub

Browse files

Files changed (3) hide show

.meta.json +3 -3
README.md +8 -3
generation_config.json +1 -1

.meta.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "safetensors": "0.8.0",
-  "torch": "2.11.0+cu128",
-  "transformers": "5.15.0.dev0",
-  "vllm": "0.24.0+cu129"
 }

 {
   "safetensors": "0.8.0",
+  "sglang": "0.5.15.post1",
+  "torch": "2.11.0+cu129",
+  "transformers": "5.12.1"
 }

README.md CHANGED Viewed

@@ -468,6 +468,11 @@ main()
 ### Test environment:
 - safetensors: 0.8.0
-- torch: 2.11.0+cu128
-- transformers: 5.15.0.dev0
-- vllm: 0.24.0+cu129

 ### Test environment:
 - safetensors: 0.8.0
+- sglang: 0.5.15.post1
+- torch: 2.11.0+cu129
+- transformers: 5.12.1
+### Change log:
+- 2026-07-15: Initial version.
+  - 2026-07-22: Added SGLang example. Updated model config so that SGLang can run.

generation_config.json CHANGED Viewed

@@ -5,5 +5,5 @@
   "eos_token_id": 1,
   "temperature": 1.0,
   "top_p": 1.0,
-  "transformers_version": "5.15.0.dev0"
 }

   "eos_token_id": 1,
   "temperature": 1.0,
   "top_p": 1.0,
+  "transformers_version": "5.12.1"
 }