leap-ie
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Weights and Biases Integration

We can also log results directly to your WandB projects. To do this, set project_name to the name of the WandB project where you'd like the results to be logged, and add your WandB API key and entity name to the config dictionary:
config = {
"wandb_api_key": "YOUR_WANDB_API_KEY",
"wandb_entity": "your_wandb_entity",
"leap_api_key": "YOUR_LEAP_API_KEY",
}
df_results, dict_results = engine.generate(
project_name="your_wandb_project_name",
model=your_model,
class_list=["hotdog", "not_hotdog"],
config=config,
)

Hugging Face

We provide a convenvience function to help you download image classification and segmentation directly from Hugging Face. To do this first import the get_model function from from leap_ie.vision.models:
from leap_ie.vision.models import get_model
Then, you can download a model by passing the name of the model to get_model:
preprocessing, model, class_list = get_model("microsoft/resnet-50", source="huggingface")
For more information on the get_model function, see the API Reference.