from grid.model.perception.vlm.molmo import Molmo
car = AirGenCar()

# We will be capturing an image from the AirGen simulator 
# and run model inference on it.

img =  car.getImage("front_center", "rgb").data

model = Molmo(use_local = False)
result = model.run(image=img, prompt=<prompt>)
print(result)
The Molmo class provides core functionality for this module.
​
class Molmo()
​
use_local
boolean
default:"False"
If True, inference call is run on the local VM, else offloaded onto GRID-Cortex. Defaults to False.
​
def run()
​
image
np.ndarray
required
The input RGB image of shape (M,N,3)(M,N,3).
​
prompt
str
required
The question to answer about the media.
​
Returns
str
The response to the prompt.
from grid.model.perception.vlm.molmo import Molmo
car = AirGenCar()

# We will be capturing an image from the AirGen simulator 
# and run model inference on it.

img =  car.getImage("front_center", "rgb").data

model = Molmo(use_local = False)
result = model.run(image=img, prompt=<prompt>)
print(result)
This code is licensed under the Apache 2.0 License.