Instructions to use UniVRModelGeneral/UniVR-34B-General with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use UniVRModelGeneral/UniVR-34B-General with Transformers:

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

pipe = pipeline("image-text-to-text", model="UniVRModelGeneral/UniVR-34B-General")

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("UniVRModelGeneral/UniVR-34B-General", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use UniVRModelGeneral/UniVR-34B-General with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "UniVRModelGeneral/UniVR-34B-General"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "UniVRModelGeneral/UniVR-34B-General",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/UniVRModelGeneral/UniVR-34B-General

SGLang

How to use UniVRModelGeneral/UniVR-34B-General 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 "UniVRModelGeneral/UniVR-34B-General" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "UniVRModelGeneral/UniVR-34B-General",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "UniVRModelGeneral/UniVR-34B-General" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "UniVRModelGeneral/UniVR-34B-General",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use UniVRModelGeneral/UniVR-34B-General with Docker Model Runner:
```
docker model run hf.co/UniVRModelGeneral/UniVR-34B-General
```

UniVR-34B-General / .gitattributes

maverickrzw

Upload 10 files

f0573de verified 27 days ago

Raw

History Blame Contribute Delete

1.8 kB

	*.7z filter=lfs diff=lfs merge=lfs -text
	*.arrow filter=lfs diff=lfs merge=lfs -text
	*.bin filter=lfs diff=lfs merge=lfs -text
	*.bz2 filter=lfs diff=lfs merge=lfs -text
	*.ckpt filter=lfs diff=lfs merge=lfs -text
	*.ftz filter=lfs diff=lfs merge=lfs -text
	*.gz filter=lfs diff=lfs merge=lfs -text
	*.h5 filter=lfs diff=lfs merge=lfs -text
	*.joblib filter=lfs diff=lfs merge=lfs -text
	.lfs. filter=lfs diff=lfs merge=lfs -text
	*.mlmodel filter=lfs diff=lfs merge=lfs -text
	*.model filter=lfs diff=lfs merge=lfs -text
	*.msgpack filter=lfs diff=lfs merge=lfs -text
	*.npy filter=lfs diff=lfs merge=lfs -text
	*.npz filter=lfs diff=lfs merge=lfs -text
	*.onnx filter=lfs diff=lfs merge=lfs -text
	*.ot filter=lfs diff=lfs merge=lfs -text
	*.parquet filter=lfs diff=lfs merge=lfs -text
	*.pb filter=lfs diff=lfs merge=lfs -text
	*.pickle filter=lfs diff=lfs merge=lfs -text
	*.pkl filter=lfs diff=lfs merge=lfs -text
	*.pt filter=lfs diff=lfs merge=lfs -text
	*.pth filter=lfs diff=lfs merge=lfs -text
	*.rar filter=lfs diff=lfs merge=lfs -text
	*.safetensors filter=lfs diff=lfs merge=lfs -text
	saved_model/*/ filter=lfs diff=lfs merge=lfs -text
	.tar. filter=lfs diff=lfs merge=lfs -text
	*.tar filter=lfs diff=lfs merge=lfs -text
	*.tflite filter=lfs diff=lfs merge=lfs -text
	*.tgz filter=lfs diff=lfs merge=lfs -text
	*.wasm filter=lfs diff=lfs merge=lfs -text
	*.xz filter=lfs diff=lfs merge=lfs -text
	*.zip filter=lfs diff=lfs merge=lfs -text
	*.zst filter=lfs diff=lfs merge=lfs -text
	tfevents filter=lfs diff=lfs merge=lfs -text
	asset/Draw.png filter=lfs diff=lfs merge=lfs -text
	asset/Fig1_v1.png filter=lfs diff=lfs merge=lfs -text
	asset/okra.png filter=lfs diff=lfs merge=lfs -text
	asset/robot_eval_02.jpg filter=lfs diff=lfs merge=lfs -text
	asset/robot_eval_08.jpg filter=lfs diff=lfs merge=lfs -text