Instructions to use internlm/Intern-S2-Preview-397B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use internlm/Intern-S2-Preview-397B with Transformers:

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

pipe = pipeline("image-text-to-text", model="internlm/Intern-S2-Preview-397B", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForImageTextToText
model = AutoModelForImageTextToText.from_pretrained("internlm/Intern-S2-Preview-397B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use internlm/Intern-S2-Preview-397B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "internlm/Intern-S2-Preview-397B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "internlm/Intern-S2-Preview-397B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/internlm/Intern-S2-Preview-397B

SGLang

How to use internlm/Intern-S2-Preview-397B 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 "internlm/Intern-S2-Preview-397B" \
    --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": "internlm/Intern-S2-Preview-397B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "internlm/Intern-S2-Preview-397B" \
        --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": "internlm/Intern-S2-Preview-397B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use internlm/Intern-S2-Preview-397B with Docker Model Runner:
```
docker model run hf.co/internlm/Intern-S2-Preview-397B
```

Add community evaluation results for Terminal-Bench 2.1, MMLU-Pro, SWE-Bench Pro, SWE-bench Multilingual, HMMT February 2026

by nielsr HF Staff - opened about 18 hours ago

base: refs/heads/main

←

from: refs/pr/9

Discussion Files changed

+35

-0

Files changed (5) hide show

.eval_results/hmmt_feb_2026.yaml +7 -0
.eval_results/mmlu-pro.yaml +7 -0
.eval_results/swe-bench_multilingual.yaml +7 -0
.eval_results/swe-bench_pro.yaml +7 -0
.eval_results/terminal-bench-2.1.yaml +7 -0

.eval_results/hmmt_feb_2026.yaml ADDED Viewed

	@@ -0,0 +1,7 @@

+- dataset:
+    id: MathArena/hmmt_feb_2026
+    task_id: MathArena/hmmt_feb_2026
+  value: 91.57
+  source:
+    url: https://arxiv.org/abs/2608.13505
+    name: Paper (Table 3)

.eval_results/mmlu-pro.yaml ADDED Viewed

	@@ -0,0 +1,7 @@

+- dataset:
+    id: TIGER-Lab/MMLU-Pro
+    task_id: mmlu_pro
+  value: 89.75
+  source:
+    url: https://arxiv.org/abs/2608.13505
+    name: Paper (Table 3)

.eval_results/swe-bench_multilingual.yaml ADDED Viewed

	@@ -0,0 +1,7 @@

+- dataset:
+    id: SWE-bench/SWE-bench_Multilingual
+    task_id: swe_bench_multilingual_%_resolved
+  value: 81.67
+  source:
+    url: https://arxiv.org/abs/2608.13505
+    name: Paper (Table 3)

.eval_results/swe-bench_pro.yaml ADDED Viewed

	@@ -0,0 +1,7 @@

+- dataset:
+    id: ScaleAI/SWE-bench_Pro
+    task_id: SWE_Bench_Pro
+  value: 61.56
+  source:
+    url: https://arxiv.org/abs/2608.13505
+    name: Paper (Table 3)

.eval_results/terminal-bench-2.1.yaml ADDED Viewed

	@@ -0,0 +1,7 @@

+- dataset:
+    id: harborframework/terminal-bench-2.1
+    task_id: terminalbench_2_1
+  value: 67.42
+  source:
+    url: https://arxiv.org/abs/2608.13505
+    name: Paper (Table 3)