Generalist model to generate future world state as videos from text and image prompts to create synthetic training data for robots and autonomous vehicles.
Follow the steps below to download and run the NVIDIA NIM inference microservice for this model on your infrastructure of choice.
$ docker login nvcr.io
Username: $oauthtoken
Password: <PASTE_API_KEY_HERE>
Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.
export NGC_API_KEY=<PASTE_API_KEY_HERE>
export LOCAL_NIM_CACHE=~/.cache/nim
mkdir -p "$LOCAL_NIM_CACHE"
docker run -it --rm \
--gpus all \
--ipc host \
-e NGC_API_KEY \
-v "$LOCAL_NIM_CACHE:/opt/nim/.cache" \
-u $(id -u) \
-p 8000:8000 \
nvcr.io/nim/nvidia/cosmos-predict1-7b-text2world:latest
You can now make a local API call using this curl command:
curl -X 'POST' \
'http://0.0.0.0:8000/v1/infer' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"prompt": "first person view from a camera in a car driving down a two lane neighborhood street, viewed from the dashcam as we drive down the street. The camera faces forward. There are nice houses and sidewalks in this suburban area with green grass front yards and flower gardens and large oak trees. It is a rainy day and there are grey clouds overhead. The road has puddles on it, reflecting the sky overhead. The windshield wipers flash by.",
"seed": 4
}'
For more details on getting started with this NIM, visit the NVIDIA NIM Docs.