Instructions to use naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B with Transformers:

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

pipe = pipeline("text-generation", model="naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-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": "naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B

SGLang

How to use naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-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 "naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-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": "naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-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": "naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B with Docker Model Runner:
```
docker model run hf.co/naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B
```

DongHyunKim commited on Apr 24, 2025

Commit

0d880ef

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Update README.md

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@@ -69,11 +69,15 @@ Although HyperCLOVAX-SEED-Vision-Instruct-3B is a lightweight model, it is capab
 | InternV-2-4B                      | 4096 tokens, 16 frames         | 33.8           | 36.0                | 22.8               | 54.2                  | 52.0                 | 22.7       | 83.0              | 76.9              | 51.6                     | 46.11                  | 39.75                  | 42.58                |
 | InternV-2-8B                      | 4096 tokens, 16 frames         | 43.7           | 41.2                | 32.4               | 58.5                  | 53.2                 | 28.5       | 86.6              | 79.0              | 97.0                     | 50.32                  | 45.79                  | 47.81                |
 ## Example
 ```python
 import argparse
-import importlib.util
 import os
 import sys
 from uuid import uuid4

 | InternV-2-4B                      | 4096 tokens, 16 frames         | 33.8           | 36.0                | 22.8               | 54.2                  | 52.0                 | 22.7       | 83.0              | 76.9              | 51.6                     | 46.11                  | 39.75                  | 42.58                |
 | InternV-2-8B                      | 4096 tokens, 16 frames         | 43.7           | 41.2                | 32.4               | 58.5                  | 53.2                 | 28.5       | 86.6              | 79.0              | 97.0                     | 50.32                  | 45.79                  | 47.81                |
+## Dependencies for Processor
+- [av](https://github.com/PyAV-Org/PyAV)
+- [decord](https://github.com/dmlc/decord)
 ## Example
 ```python
 import argparse
+import importlib
 import os
 import sys
 from uuid import uuid4