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ImageQnAModel(model_id: str, endpoint_name: typing.Optional[str] = None)
Answers questions about an image.
Examples::
model = ImageQnAModel.from_pretrained("imagetext@001")
image = Image.load_from_file("image.png")
answers = model.ask_question(
image=image,
question="What color is the car in this image?",
# Optional:
number_of_results=1,
)
Methods
ImageQnAModel
ImageQnAModel(model_id: str, endpoint_name: typing.Optional[str] = None)
Creates a _ModelGardenModel.
This constructor should not be called directly.
Use {model_class}.from_pretrained(model_name=...)
instead.
Parameters | |
---|---|
Name | Description |
model_id |
str
Identifier of a Model Garden Model. Example: "text-bison@001" |
endpoint_name |
typing.Optional[str]
Vertex Endpoint resource name for the model |
ask_question
ask_question(
image: vertexai.vision_models.Image, question: str, *, number_of_results: int = 1
) -> typing.List[str]
Answers questions about an image.
Parameters | |
---|---|
Name | Description |
image |
Image
The image to get captions for. Size limit: 10 MB. |
question |
str
Question to ask about the image. |
from_pretrained
from_pretrained(model_name: str) -> vertexai._model_garden._model_garden_models.T
Loads a _ModelGardenModel.
Parameter | |
---|---|
Name | Description |
model_name |
str
Name of the model. |
Exceptions | |
---|---|
Type | Description |
ValueError |
If model_name is unknown. |
ValueError |
If model does not support this class. |