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

Libraries

How to use internlm/Intern-S2-Preview 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", 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)

# Load model directly
from transformers import AutoModelForImageTextToText
model = AutoModelForImageTextToText.from_pretrained("internlm/Intern-S2-Preview", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use internlm/Intern-S2-Preview 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"
# 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",
		"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

SGLang

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

Intern-S2-Preview

File size: 4,422 Bytes

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{
  "model_type": "intern_s2_preview",
  "architectures": [
    "InternS2PreviewForConditionalGeneration"
  ],
  "transformers_version": "5.2.0",
  "auto_map": {
    "AutoConfig": "configuration_interns2_preview.InternS2PreviewConfig",
    "AutoModelForCausalLM": "modeling_interns2_preview.InternS2PreviewForCausalLM",
    "AutoModel": "modeling_interns2_preview.InternS2PreviewModel",
    "AutoModelForImageTextToText": "modeling_interns2_preview.InternS2PreviewForConditionalGeneration",
    "AutoModelForMultimodalLM": "modeling_interns2_preview.InternS2PreviewForConditionalGeneration"
  },
  "image_token_id": 248056,
  "text_config": {
    "model_type": "qwen3_5_moe_text",
    "attention_bias": false,
    "attention_dropout": 0.0,
    "attn_output_gate": true,
    "dtype": "bfloat16",
    "eos_token_id": 248044,
    "full_attention_interval": 4,
    "head_dim": 256,
    "hidden_act": "silu",
    "hidden_size": 2048,
    "initializer_range": 0.02,
    "layer_types": [
      "linear_attention",
      "linear_attention",
      "linear_attention",
      "full_attention",
      "linear_attention",
      "linear_attention",
      "linear_attention",
      "full_attention",
      "linear_attention",
      "linear_attention",
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      "full_attention",
      "linear_attention",
      "linear_attention",
      "linear_attention",
      "full_attention",
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      "linear_attention",
      "full_attention",
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      "linear_attention",
      "linear_attention",
      "linear_attention",
      "full_attention"
    ],
    "linear_conv_kernel_dim": 4,
    "linear_key_head_dim": 128,
    "linear_num_key_heads": 16,
    "linear_num_value_heads": 32,
    "linear_value_head_dim": 128,
    "max_position_embeddings": 262144,
    "mlp_only_layers": [],
    "moe_intermediate_size": 512,
    "mtp_num_hidden_layers": 1,
    "mtp_use_dedicated_embeddings": false,
    "num_attention_heads": 16,
    "num_experts": 256,
    "num_experts_per_tok": 8,
    "num_hidden_layers": 40,
    "num_key_value_heads": 2,
    "rms_norm_eps": 1e-06,
    "router_aux_loss_coef": 0.001,
    "shared_expert_intermediate_size": 512,
    "use_cache": true,
    "vocab_size": 251392,
    "mamba_ssm_dtype": "float32",
    "rope_parameters": {
      "mrope_interleaved": true,
      "mrope_section": [
        11,
        11,
        10
      ],
      "rope_type": "default",
      "rope_theta": 10000000,
      "partial_rotary_factor": 0.25
    },
    "pad_token_id": null,
    "bos_token_id": null,
    "tie_word_embeddings": false,
    "output_router_logits": false,
    "partial_rotary_factor": 0.25
  },
  "tie_word_embeddings": false,
  "video_token_id": 248057,
  "vision_config": {
    "model_type": "intern_s2_preview",
    "deepstack_visual_indexes": [],
    "depth": 27,
    "hidden_act": "gelu_pytorch_tanh",
    "hidden_size": 1152,
    "in_channels": 3,
    "initializer_range": 0.02,
    "intermediate_size": 4304,
    "num_heads": 16,
    "num_position_embeddings": 2304,
    "out_hidden_size": 2048,
    "patch_size": 16,
    "spatial_merge_size": 2,
    "temporal_patch_size": 2
  },
  "vision_end_token_id": 248054,
  "vision_start_token_id": 248053,
  "ts_config": {
    "model_type": "interns2_preview_time_series",
    "auto_map": {
      "AutoConfig": "configuration_interns2_preview.InternS2PreviewTimeSeriesConfig",
      "AutoModel": "modeling_interns2_preview.InternS2PreviewTimeSeriesModel"
    },
    "activation_dropout": 0.0,
    "activation_function": "gelu",
    "attention_dropout": 0.0,
    "d_model": 768,
    "dropout": 0.0,
    "encoder_attention_heads": 8,
    "encoder_ffn_dim": 3072,
    "encoder_layerdrop": 0.0,
    "encoder_layers": 17,
    "max_source_positions": 1500,
    "num_mel_bins": 80,
    "out_hidden_size": 2048,
    "scale_embedding": false,
    "ts_adapt_in_dim": 256,
    "ts_adapt_out_dim": 1024,
    "ts_hidden_dim": 1024
  },
  "ts_token_id": 248093,
  "ts_start_id": 248091,
  "ts_end_id": 248092
}