Image-Text-to-Text
Transformers
Safetensors
English
openvla
feature-extraction
robotics
vla
multimodal
pretraining
custom_code
Instructions to use openvla/openvla-v01-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openvla/openvla-v01-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="openvla/openvla-v01-7b", trust_remote_code=True)# Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("openvla/openvla-v01-7b", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use openvla/openvla-v01-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openvla/openvla-v01-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openvla/openvla-v01-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/openvla/openvla-v01-7b
- SGLang
How to use openvla/openvla-v01-7b 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 "openvla/openvla-v01-7b" \ --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": "openvla/openvla-v01-7b", "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 "openvla/openvla-v01-7b" \ --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": "openvla/openvla-v01-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use openvla/openvla-v01-7b with Docker Model Runner:
docker model run hf.co/openvla/openvla-v01-7b
File size: 1,074 Bytes
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"auto_map": {
"AutoImageProcessor": "processing_prismatic.PrismaticImageProcessor",
"AutoProcessor": "processing_prismatic.PrismaticProcessor"
},
"image_processor_type": "PrismaticImageProcessor",
"image_resize_strategy": "letterbox",
"input_sizes": [
[
3,
224,
224
]
],
"interpolations": [
"bicubic"
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"means": [
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0.5,
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]
],
"processor_class": "PrismaticProcessor",
"stds": [
[
0.5,
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]
],
"tvf_crop_params": [
{
"output_size": [
224,
224
]
}
],
"tvf_do_letterbox": true,
"tvf_letterbox_fill": [
127,
127,
127
],
"tvf_normalize_params": [
{
"inplace": false,
"mean": [
0.5,
0.5,
0.5
],
"std": [
0.5,
0.5,
0.5
]
}
],
"tvf_resize_params": [
{
"antialias": true,
"interpolation": 3,
"max_size": null,
"size": 224
}
],
"use_fused_vision_backbone": false
}
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