Instructions to use deepseek-ai/DeepSeek-V4.1-Flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use deepseek-ai/DeepSeek-V4.1-Flash with Transformers:

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

pipe = pipeline("image-text-to-text", model="deepseek-ai/DeepSeek-V4.1-Flash")

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-V4.1-Flash", device_map="auto")

Inference
HuggingChat
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use deepseek-ai/DeepSeek-V4.1-Flash with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "deepseek-ai/DeepSeek-V4.1-Flash"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "deepseek-ai/DeepSeek-V4.1-Flash",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/deepseek-ai/DeepSeek-V4.1-Flash

SGLang

How to use deepseek-ai/DeepSeek-V4.1-Flash 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 "deepseek-ai/DeepSeek-V4.1-Flash" \
    --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": "deepseek-ai/DeepSeek-V4.1-Flash",
		"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 "deepseek-ai/DeepSeek-V4.1-Flash" \
        --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": "deepseek-ai/DeepSeek-V4.1-Flash",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use deepseek-ai/DeepSeek-V4.1-Flash with Docker Model Runner:
```
docker model run hf.co/deepseek-ai/DeepSeek-V4.1-Flash
```

Add ExtractBench evaluation results

#45

by boyang-runllama - opened 2 days ago

base: refs/heads/main

←

from: refs/pr/45

Discussion Files changed

+40

-0

Files changed (1) hide show

.eval_results/extractbench.yaml +40 -0

.eval_results/extractbench.yaml ADDED Viewed

	@@ -0,0 +1,40 @@

+- dataset:
+    id: llamaindex/ExtractBench
+    task_id: mean
+  value: 87.11
+  date: '2026-09-11'
+  source:
+    url: https://huggingface.co/datasets/llamaindex/ExtractBench
+    name: ExtractBench
+    user: boyang-runllama
+  notes: "Pipeline name: deepseek_v4_1_flash_extract_oneshot_structured_output_file (served via the DeepSeek API, thinking disabled)"
+- dataset:
+    id: llamaindex/ExtractBench
+    task_id: short
+  value: 94.44
+  date: '2026-09-11'
+  source:
+    url: https://huggingface.co/datasets/llamaindex/ExtractBench
+    name: ExtractBench
+    user: boyang-runllama
+  notes: "Pipeline name: deepseek_v4_1_flash_extract_oneshot_structured_output_file (served via the DeepSeek API, thinking disabled)"
+- dataset:
+    id: llamaindex/ExtractBench
+    task_id: medium
+  value: 81.49
+  date: '2026-09-11'
+  source:
+    url: https://huggingface.co/datasets/llamaindex/ExtractBench
+    name: ExtractBench
+    user: boyang-runllama
+  notes: "Pipeline name: deepseek_v4_1_flash_extract_oneshot_structured_output_file (served via the DeepSeek API, thinking disabled)"
+- dataset:
+    id: llamaindex/ExtractBench
+    task_id: long
+  value: 22.23
+  date: '2026-09-11'
+  source:
+    url: https://huggingface.co/datasets/llamaindex/ExtractBench
+    name: ExtractBench
+    user: boyang-runllama
+  notes: "Pipeline name: deepseek_v4_1_flash_extract_oneshot_structured_output_file (served via the DeepSeek API, thinking disabled)"