Instructions to use utter-project/TowerVision-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use utter-project/TowerVision-2B with Transformers:

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

pipe = pipeline("image-text-to-text", model="utter-project/TowerVision-2B")
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("utter-project/TowerVision-2B")
model = AutoModelForImageTextToText.from_pretrained("utter-project/TowerVision-2B")
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

vLLM

How to use utter-project/TowerVision-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "utter-project/TowerVision-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "utter-project/TowerVision-2B",
		"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/utter-project/TowerVision-2B

SGLang

How to use utter-project/TowerVision-2B 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 "utter-project/TowerVision-2B" \
    --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": "utter-project/TowerVision-2B",
		"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 "utter-project/TowerVision-2B" \
        --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": "utter-project/TowerVision-2B",
		"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 utter-project/TowerVision-2B with Docker Model Runner:
```
docker model run hf.co/utter-project/TowerVision-2B
```

Guilherme Viveiros commited on Aug 20, 2025

Commit

925ec98

verified ·

1 Parent(s): a8eba42

Upload processor

Browse files

Files changed (3) hide show

added_tokens.json +1 -3
special_tokens_map.json +1 -1
tokenizer_config.json +2 -2

added_tokens.json CHANGED Viewed

@@ -1,5 +1,3 @@
 {
-  "<image>": 256000,
-  "<|im_end|>": 256002,
-  "<|im_start|>": 256001
 }

 {
+  "<image>": 256000
 }

special_tokens_map.json CHANGED Viewed

@@ -11,7 +11,7 @@
     "single_word": false
   },
   "eos_token": {
-    "content": "<end_of_turn>",
     "lstrip": false,
     "normalized": false,
     "rstrip": false,

     "single_word": false
   },
   "eos_token": {
+    "content": "<eos>",
     "lstrip": false,
     "normalized": false,
     "rstrip": false,

tokenizer_config.json CHANGED Viewed

@@ -2009,7 +2009,7 @@
   ],
   "bos_token": "<bos>",
   "clean_up_tokenization_spaces": false,
-  "eos_token": "<end_of_turn>",
   "extra_special_tokens": {},
   "model_max_length": 8192,
   "pad_token": "<unk>",
@@ -2017,7 +2017,7 @@
   "processor_class": "LlavaNextProcessor",
   "sp_model_kwargs": {},
   "spaces_between_special_tokens": false,
-  "tokenizer_class": "GemmaTokenizerFast",
   "unk_token": "<unk>",
   "use_default_system_prompt": false
 }

   ],
   "bos_token": "<bos>",
   "clean_up_tokenization_spaces": false,
+  "eos_token": "<eos>",
   "extra_special_tokens": {},
   "model_max_length": 8192,
   "pad_token": "<unk>",
   "processor_class": "LlavaNextProcessor",
   "sp_model_kwargs": {},
   "spaces_between_special_tokens": false,
+  "tokenizer_class": "GemmaTokenizer",
   "unk_token": "<unk>",
   "use_default_system_prompt": false
 }