Instructions to use nvidia/LocateAnything-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nvidia/LocateAnything-3B with Transformers:

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

pipe = pipeline("image-text-to-text", model="nvidia/LocateAnything-3B", 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 AutoModel
model = AutoModel.from_pretrained("nvidia/LocateAnything-3B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use nvidia/LocateAnything-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nvidia/LocateAnything-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nvidia/LocateAnything-3B",
		"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/nvidia/LocateAnything-3B

SGLang

How to use nvidia/LocateAnything-3B 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 "nvidia/LocateAnything-3B" \
    --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": "nvidia/LocateAnything-3B",
		"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 "nvidia/LocateAnything-3B" \
        --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": "nvidia/LocateAnything-3B",
		"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 nvidia/LocateAnything-3B with Docker Model Runner:
```
docker model run hf.co/nvidia/LocateAnything-3B
```

NotImplementedError: self._attn_implementation='flash_attention_2'

#18

by phamvantoan - opened 1 day ago

Discussion

phamvantoan

1 day ago

Hi,

Thank you for your valuable contribution about Locate Anything model

When testing this model, I got an error as follows:

Firstly, I run this model under an environment without flash-attn package. Then, when running, attention is automatically switched to "sdpa" attention and the code runs as normal.

However, when installing flash-attn in my environment using package "flash_attn-2.8.3+cu12torch2.7cxx11abiFALSE-cp311-cp311-linux_x86_64.whl"
(my torch version is 2.7.0+cu126 and python 3.11), I got an error when running the same code

File "/home/quadrep/.cache/huggingface/modules/transformers_modules/weights/modeling_qwen2.py", line 1335, in forward
raise NotImplementedError(f'{self._attn_implementation=}')
NotImplementedError: self._attn_implementation='flash_attention_2'

Because I am focusing on computation time and occupied VRAM, I want to try using flash-attn if it helps

Could you please let me know what my problem is and how to fix it?

Marvs25

about 18 hours ago

Test comment

ShihaoW

NVIDIA org about 14 hours ago

Hi there!

Thank you so much for your interest and for testing out the Locate Anything model!

To answer your question: the hybrid and fast modes in Locate Anything currently only support Magi Attention and do not support Flash Attention (specifically, only the MoonViT component can use Flash Attention, but the LLM component cannot).

If your hardware supports Magi Attention, please definitely give it a try!

I completely understand your concerns about computation time and VRAM, as sdpa and eager modes do consume quite a lot of memory. To help solve this, I am currently working on adding Flex Attention support to the language model. I really hope this update will be helpful for your VRAM usage in the near future!

Please let me know if you have any other questions. Happy coding!
@phamvantoan

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