Instructions to use HuggingFaceTB/SmolVLM2-500M-Video-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HuggingFaceTB/SmolVLM2-500M-Video-Instruct with Transformers:

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

pipe = pipeline("image-text-to-text", model="HuggingFaceTB/SmolVLM2-500M-Video-Instruct")
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 AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("HuggingFaceTB/SmolVLM2-500M-Video-Instruct")
model = AutoModelForImageTextToText.from_pretrained("HuggingFaceTB/SmolVLM2-500M-Video-Instruct")
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?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use HuggingFaceTB/SmolVLM2-500M-Video-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HuggingFaceTB/SmolVLM2-500M-Video-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HuggingFaceTB/SmolVLM2-500M-Video-Instruct",
		"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/HuggingFaceTB/SmolVLM2-500M-Video-Instruct

SGLang

How to use HuggingFaceTB/SmolVLM2-500M-Video-Instruct 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 "HuggingFaceTB/SmolVLM2-500M-Video-Instruct" \
    --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": "HuggingFaceTB/SmolVLM2-500M-Video-Instruct",
		"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 "HuggingFaceTB/SmolVLM2-500M-Video-Instruct" \
        --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": "HuggingFaceTB/SmolVLM2-500M-Video-Instruct",
		"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 HuggingFaceTB/SmolVLM2-500M-Video-Instruct with Docker Model Runner:
```
docker model run hf.co/HuggingFaceTB/SmolVLM2-500M-Video-Instruct
```

RaushanTurganbay HF Staff commited on Feb 13, 2025

Commit

2fb535e

verified ·

1 Parent(s): 82fc17e

Upload processor

Browse files

Files changed (3) hide show

preprocessor_config.json +8 -6
special_tokens_map.json +7 -21
tokenizer_config.json +11 -2

preprocessor_config.json CHANGED Viewed

@@ -10,7 +10,7 @@
     0.5,
     0.5
   ],
-  "image_processor_type": "Idefics3ImageProcessor",
   "image_std": [
     0.5,
     0.5,
@@ -19,15 +19,17 @@
   "max_image_size": {
     "longest_edge": 512
   },
-  "video_sampling": {
-    "fps": 1,
-    "max_frames": 64,
-    "video_size": {"longest_edge": 384}
-  },
   "processor_class": "SmolVLMProcessor",
   "resample": 1,
   "rescale_factor": 0.00392156862745098,
   "size": {
     "longest_edge": 2048
   }
 }

     0.5,
     0.5
   ],
+  "image_processor_type": "SmolVLMImageProcessor",
   "image_std": [
     0.5,
     0.5,
   "max_image_size": {
     "longest_edge": 512
   },
   "processor_class": "SmolVLMProcessor",
   "resample": 1,
   "rescale_factor": 0.00392156862745098,
   "size": {
     "longest_edge": 2048
+  },
+  "video_sampling": {
+    "fps": 1,
+    "max_frames": 64,
+    "video_size": {
+      "longest_edge": 384
+    }
   }
 }

special_tokens_map.json CHANGED Viewed

@@ -1,26 +1,8 @@
 {
   "additional_special_tokens": [
-    {
-      "content": "<fake_token_around_image>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false
-    },
-    {
-      "content": "<image>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false
-    },
-    {
-      "content": "<end_of_utterance>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false
-    }
   ],
   "bos_token": {
     "content": "<|im_start|>",
@@ -29,6 +11,7 @@
     "rstrip": false,
     "single_word": false
   },
   "eos_token": {
     "content": "<end_of_utterance>",
     "lstrip": false,
@@ -36,6 +19,9 @@
     "rstrip": false,
     "single_word": false
   },
   "pad_token": {
     "content": "<|im_end|>",
     "lstrip": false,

 {
   "additional_special_tokens": [
+    "<fake_token_around_image>",
+    "<image>",
+    "<end_of_utterance>"
   ],
   "bos_token": {
     "content": "<|im_start|>",
     "rstrip": false,
     "single_word": false
   },
+  "end_of_utterance_token": "<end_of_utterance>",
   "eos_token": {
     "content": "<end_of_utterance>",
     "lstrip": false,
     "rstrip": false,
     "single_word": false
   },
+  "fake_image_token": "<fake_token_around_image>",
+  "global_image_token": "<global-img>",
+  "image_token": "<image>",
   "pad_token": {
     "content": "<|im_end|>",
     "lstrip": false,

tokenizer_config.json CHANGED Viewed

@@ -1170,12 +1170,21 @@
   "bos_token": "<|im_start|>",
   "chat_template": "<|im_start|>{% for message in messages %}{{message['role'] | capitalize}}{% if message['content'][0]['type'] == 'image' %}{{':'}}{% else %}{{': '}}{% endif %}{% for line in message['content'] %}{% if line['type'] == 'text' %}{{line['text']}}{% elif line['type'] == 'image' %}{{ '<image>' }}{% endif %}{% endfor %}<end_of_utterance>\n{% endfor %}{% if add_generation_prompt %}{{ 'Assistant:' }}{% endif %}",
   "clean_up_tokenization_spaces": false,
   "eos_token": "<end_of_utterance>",
-  "extra_special_tokens": {},
   "legacy": false,
   "model_max_length": 8192,
   "pad_token": "<|im_end|>",
-  "processor_class": "Idefics3Processor",
   "tokenizer_class": "GPT2Tokenizer",
   "truncation_side": "left",
   "unk_token": "<|endoftext|>",

   "bos_token": "<|im_start|>",
   "chat_template": "<|im_start|>{% for message in messages %}{{message['role'] | capitalize}}{% if message['content'][0]['type'] == 'image' %}{{':'}}{% else %}{{': '}}{% endif %}{% for line in message['content'] %}{% if line['type'] == 'text' %}{{line['text']}}{% elif line['type'] == 'image' %}{{ '<image>' }}{% endif %}{% endfor %}<end_of_utterance>\n{% endfor %}{% if add_generation_prompt %}{{ 'Assistant:' }}{% endif %}",
   "clean_up_tokenization_spaces": false,
+  "end_of_utterance_token": "<end_of_utterance>",
   "eos_token": "<end_of_utterance>",
+  "extra_special_tokens": {
+    "end_of_utterance_token": "<end_of_utterance>",
+    "fake_image_token": "<fake_token_around_image>",
+    "global_image_token": "<global-img>",
+    "image_token": "<image>"
+  },
+  "fake_image_token": "<fake_token_around_image>",
+  "global_image_token": "<global-img>",
+  "image_token": "<image>",
   "legacy": false,
   "model_max_length": 8192,
   "pad_token": "<|im_end|>",
+  "processor_class": "SmolVLMProcessor",
   "tokenizer_class": "GPT2Tokenizer",
   "truncation_side": "left",
   "unk_token": "<|endoftext|>",