Instructions to use iamthe66epitaph/BabyAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamthe66epitaph/BabyAI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="iamthe66epitaph/BabyAI")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("iamthe66epitaph/BabyAI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| import datasets | |
| from ..folder_based_builder import folder_based_builder | |
| logger = datasets.utils.logging.get_logger(__name__) | |
| class VideoFolderConfig(folder_based_builder.FolderBasedBuilderConfig): | |
| """BuilderConfig for ImageFolder.""" | |
| drop_labels: bool = None | |
| drop_metadata: bool = None | |
| def __post_init__(self): | |
| super().__post_init__() | |
| class VideoFolder(folder_based_builder.FolderBasedBuilder): | |
| BASE_FEATURE = datasets.Video | |
| BASE_COLUMN_NAME = "video" | |
| BUILDER_CONFIG_CLASS = VideoFolderConfig | |
| EXTENSIONS: list[str] # definition at the bottom of the script | |
| # TODO: initial list, we should check the compatibility of other formats | |
| VIDEO_EXTENSIONS = [ | |
| ".mkv", | |
| ".mp4", | |
| ".avi", | |
| ".mpeg", | |
| ".mov", | |
| ] | |
| VideoFolder.EXTENSIONS = VIDEO_EXTENSIONS | |