djai.model.models package

DjAI base AIModel class & its subclasses.

class djai.model.models.AIModel(*args, **kwargs)

Bases: polymorphic.models.PolymorphicModel, djai.util.models._ModelWithUUIDPKAndOptionalUniqueNameAndTimestampsABC

DjAI base AIModel class.

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

cloud_ai_svcs

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

created

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

dash_ui

Decorator that converts a method with a single cls argument into a property that can be accessed directly from the class.

abstract fit(**kwargs) → Any

Fit.

get_next_by_created(*, field=<model_utils.fields.AutoCreatedField: created>, is_next=True, **kwargs)

get_next_by_modified(*, field=<model_utils.fields.AutoLastModifiedField: modified>, is_next=True, **kwargs)

get_previous_by_created(*, field=<model_utils.fields.AutoCreatedField: created>, is_next=False, **kwargs)

get_previous_by_modified(*, field=<model_utils.fields.AutoLastModifiedField: modified>, is_next=False, **kwargs)

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: outputs: |-JSON(label="AI Model Output")

modified

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

name: CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

params: django.db.models.fields.json.JSONField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

polymorphic_ctype

The model field that stores the ContentType reference to the actual class.

polymorphic_ctype_id

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

abstract predict(**kwargs) → Any

Predict.

pretrained_hugging_face_transformers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_keras_imagenet_classifiers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

subclass_full_qual_names = ['djai.model.models.base._AIModelWithArtifactFilesABC', 'djai.model.models.ml.skl.SKLModel', 'djai.model.models.ml.keras.base.KerasModel', 'djai.model.models.ml.base._PreTrainedMLModelABC', 'djai.model.models.ml.keras.pre_trained.vision.image_classification.PreTrainedKerasImageNetClassifier', 'djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer', 'djai.model.models.ml.hugging_face.audio_classification.PreTrainedHuggingFaceAudioClassifier', 'djai.model.models.ml.hugging_face.image_classification.PreTrainedHuggingFaceImageClassifier', 'djai.model.models.ml.hugging_face.mask_filling.PreTrainedHuggingFaceMaskFiller', 'djai.model.models.ml.hugging_face.object_detection.PreTrainedHuggingFaceObjectDetector', 'djai.model.models.ml.hugging_face.question_answering.PreTrainedHuggingFaceQuestionAnswerer', 'djai.model.models.ml.hugging_face.speech_recognition.PreTrainedHuggingFaceSpeechRecognizer', 'djai.model.models.ml.hugging_face.table_question_answering.PreTrainedHuggingFaceTableQuestionAnswerer', 'djai.model.models.ml.hugging_face.text_classification.PreTrainedHuggingFaceTextClassifier', 'djai.model.models.ml.hugging_face.text_generation.PreTrainedHuggingFaceTextGenerator', 'djai.model.models.ml.hugging_face.text2text_generation.PreTrainedHuggingFaceText2TextGenerator', 'djai.model.models.ml.hugging_face.text_summarization.PreTrainedHuggingFaceTextSummarizer', 'djai.model.models.ml.hugging_face.token_classification.PreTrainedHuggingFaceTokenClassifier', 'djai.model.models.ml.hugging_face.translation.PreTrainedHuggingFaceTranslator', 'djai.model.models.ml.hugging_face.zero_shot_classification.PreTrainedHuggingFaceZeroShotClassifier', 'djai.model.models.ml.torch.base.TorchModel', 'djai.model.models.cloud_ai_svc.base.CloudAIService', 'djai.model.models.cloud_ai_svc.google.translation.GoogleTranslate']

subclass_names = ['_AIModelWithArtifactFilesABC', 'SKLModel', 'KerasModel', '_PreTrainedMLModelABC', 'PreTrainedKerasImageNetClassifier', 'PreTrainedHuggingFaceTransformer', 'PreTrainedHuggingFaceAudioClassifier', 'PreTrainedHuggingFaceImageClassifier', 'PreTrainedHuggingFaceMaskFiller', 'PreTrainedHuggingFaceObjectDetector', 'PreTrainedHuggingFaceQuestionAnswerer', 'PreTrainedHuggingFaceSpeechRecognizer', 'PreTrainedHuggingFaceTableQuestionAnswerer', 'PreTrainedHuggingFaceTextClassifier', 'PreTrainedHuggingFaceTextGenerator', 'PreTrainedHuggingFaceText2TextGenerator', 'PreTrainedHuggingFaceTextSummarizer', 'PreTrainedHuggingFaceTokenClassifier', 'PreTrainedHuggingFaceTranslator', 'PreTrainedHuggingFaceZeroShotClassifier', 'TorchModel', 'CloudAIService', 'GoogleTranslate']

subclasses = [<class 'djai.model.models.base._AIModelWithArtifactFilesABC'>, <class 'djai.model.models.ml.skl.SKLModel'>, <class 'djai.model.models.ml.keras.base.KerasModel'>, <class 'djai.model.models.ml.base._PreTrainedMLModelABC'>, <class 'djai.model.models.ml.keras.pre_trained.vision.image_classification.PreTrainedKerasImageNetClassifier'>, <class 'djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer'>, <class 'djai.model.models.ml.hugging_face.audio_classification.PreTrainedHuggingFaceAudioClassifier'>, <class 'djai.model.models.ml.hugging_face.image_classification.PreTrainedHuggingFaceImageClassifier'>, <class 'djai.model.models.ml.hugging_face.mask_filling.PreTrainedHuggingFaceMaskFiller'>, <class 'djai.model.models.ml.hugging_face.object_detection.PreTrainedHuggingFaceObjectDetector'>, <class 'djai.model.models.ml.hugging_face.question_answering.PreTrainedHuggingFaceQuestionAnswerer'>, <class 'djai.model.models.ml.hugging_face.speech_recognition.PreTrainedHuggingFaceSpeechRecognizer'>, <class 'djai.model.models.ml.hugging_face.table_question_answering.PreTrainedHuggingFaceTableQuestionAnswerer'>, <class 'djai.model.models.ml.hugging_face.text_classification.PreTrainedHuggingFaceTextClassifier'>, <class 'djai.model.models.ml.hugging_face.text_generation.PreTrainedHuggingFaceTextGenerator'>, <class 'djai.model.models.ml.hugging_face.text2text_generation.PreTrainedHuggingFaceText2TextGenerator'>, <class 'djai.model.models.ml.hugging_face.text_summarization.PreTrainedHuggingFaceTextSummarizer'>, <class 'djai.model.models.ml.hugging_face.token_classification.PreTrainedHuggingFaceTokenClassifier'>, <class 'djai.model.models.ml.hugging_face.translation.PreTrainedHuggingFaceTranslator'>, <class 'djai.model.models.ml.hugging_face.zero_shot_classification.PreTrainedHuggingFaceZeroShotClassifier'>, <class 'djai.model.models.ml.torch.base.TorchModel'>, <class 'djai.model.models.cloud_ai_svc.base.CloudAIService'>, <class 'djai.model.models.cloud_ai_svc.google.translation.GoogleTranslate'>]

subclasses_by_full_qual_name = {'djai.model.models.base._AIModelWithArtifactFilesABC': <class 'djai.model.models.base._AIModelWithArtifactFilesABC'>, 'djai.model.models.cloud_ai_svc.base.CloudAIService': <class 'djai.model.models.cloud_ai_svc.base.CloudAIService'>, 'djai.model.models.cloud_ai_svc.google.translation.GoogleTranslate': <class 'djai.model.models.cloud_ai_svc.google.translation.GoogleTranslate'>, 'djai.model.models.ml.base._PreTrainedMLModelABC': <class 'djai.model.models.ml.base._PreTrainedMLModelABC'>, 'djai.model.models.ml.hugging_face.audio_classification.PreTrainedHuggingFaceAudioClassifier': <class 'djai.model.models.ml.hugging_face.audio_classification.PreTrainedHuggingFaceAudioClassifier'>, 'djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer': <class 'djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer'>, 'djai.model.models.ml.hugging_face.image_classification.PreTrainedHuggingFaceImageClassifier': <class 'djai.model.models.ml.hugging_face.image_classification.PreTrainedHuggingFaceImageClassifier'>, 'djai.model.models.ml.hugging_face.mask_filling.PreTrainedHuggingFaceMaskFiller': <class 'djai.model.models.ml.hugging_face.mask_filling.PreTrainedHuggingFaceMaskFiller'>, 'djai.model.models.ml.hugging_face.object_detection.PreTrainedHuggingFaceObjectDetector': <class 'djai.model.models.ml.hugging_face.object_detection.PreTrainedHuggingFaceObjectDetector'>, 'djai.model.models.ml.hugging_face.question_answering.PreTrainedHuggingFaceQuestionAnswerer': <class 'djai.model.models.ml.hugging_face.question_answering.PreTrainedHuggingFaceQuestionAnswerer'>, 'djai.model.models.ml.hugging_face.speech_recognition.PreTrainedHuggingFaceSpeechRecognizer': <class 'djai.model.models.ml.hugging_face.speech_recognition.PreTrainedHuggingFaceSpeechRecognizer'>, 'djai.model.models.ml.hugging_face.table_question_answering.PreTrainedHuggingFaceTableQuestionAnswerer': <class 'djai.model.models.ml.hugging_face.table_question_answering.PreTrainedHuggingFaceTableQuestionAnswerer'>, 'djai.model.models.ml.hugging_face.text2text_generation.PreTrainedHuggingFaceText2TextGenerator': <class 'djai.model.models.ml.hugging_face.text2text_generation.PreTrainedHuggingFaceText2TextGenerator'>, 'djai.model.models.ml.hugging_face.text_classification.PreTrainedHuggingFaceTextClassifier': <class 'djai.model.models.ml.hugging_face.text_classification.PreTrainedHuggingFaceTextClassifier'>, 'djai.model.models.ml.hugging_face.text_generation.PreTrainedHuggingFaceTextGenerator': <class 'djai.model.models.ml.hugging_face.text_generation.PreTrainedHuggingFaceTextGenerator'>, 'djai.model.models.ml.hugging_face.text_summarization.PreTrainedHuggingFaceTextSummarizer': <class 'djai.model.models.ml.hugging_face.text_summarization.PreTrainedHuggingFaceTextSummarizer'>, 'djai.model.models.ml.hugging_face.token_classification.PreTrainedHuggingFaceTokenClassifier': <class 'djai.model.models.ml.hugging_face.token_classification.PreTrainedHuggingFaceTokenClassifier'>, 'djai.model.models.ml.hugging_face.translation.PreTrainedHuggingFaceTranslator': <class 'djai.model.models.ml.hugging_face.translation.PreTrainedHuggingFaceTranslator'>, 'djai.model.models.ml.hugging_face.zero_shot_classification.PreTrainedHuggingFaceZeroShotClassifier': <class 'djai.model.models.ml.hugging_face.zero_shot_classification.PreTrainedHuggingFaceZeroShotClassifier'>, 'djai.model.models.ml.keras.base.KerasModel': <class 'djai.model.models.ml.keras.base.KerasModel'>, 'djai.model.models.ml.keras.pre_trained.vision.image_classification.PreTrainedKerasImageNetClassifier': <class 'djai.model.models.ml.keras.pre_trained.vision.image_classification.PreTrainedKerasImageNetClassifier'>, 'djai.model.models.ml.skl.SKLModel': <class 'djai.model.models.ml.skl.SKLModel'>, 'djai.model.models.ml.torch.base.TorchModel': <class 'djai.model.models.ml.torch.base.TorchModel'>}

subclasses_by_name = {'CloudAIService': <class 'djai.model.models.cloud_ai_svc.base.CloudAIService'>, 'GoogleTranslate': <class 'djai.model.models.cloud_ai_svc.google.translation.GoogleTranslate'>, 'KerasModel': <class 'djai.model.models.ml.keras.base.KerasModel'>, 'PreTrainedHuggingFaceAudioClassifier': <class 'djai.model.models.ml.hugging_face.audio_classification.PreTrainedHuggingFaceAudioClassifier'>, 'PreTrainedHuggingFaceImageClassifier': <class 'djai.model.models.ml.hugging_face.image_classification.PreTrainedHuggingFaceImageClassifier'>, 'PreTrainedHuggingFaceMaskFiller': <class 'djai.model.models.ml.hugging_face.mask_filling.PreTrainedHuggingFaceMaskFiller'>, 'PreTrainedHuggingFaceObjectDetector': <class 'djai.model.models.ml.hugging_face.object_detection.PreTrainedHuggingFaceObjectDetector'>, 'PreTrainedHuggingFaceQuestionAnswerer': <class 'djai.model.models.ml.hugging_face.question_answering.PreTrainedHuggingFaceQuestionAnswerer'>, 'PreTrainedHuggingFaceSpeechRecognizer': <class 'djai.model.models.ml.hugging_face.speech_recognition.PreTrainedHuggingFaceSpeechRecognizer'>, 'PreTrainedHuggingFaceTableQuestionAnswerer': <class 'djai.model.models.ml.hugging_face.table_question_answering.PreTrainedHuggingFaceTableQuestionAnswerer'>, 'PreTrainedHuggingFaceText2TextGenerator': <class 'djai.model.models.ml.hugging_face.text2text_generation.PreTrainedHuggingFaceText2TextGenerator'>, 'PreTrainedHuggingFaceTextClassifier': <class 'djai.model.models.ml.hugging_face.text_classification.PreTrainedHuggingFaceTextClassifier'>, 'PreTrainedHuggingFaceTextGenerator': <class 'djai.model.models.ml.hugging_face.text_generation.PreTrainedHuggingFaceTextGenerator'>, 'PreTrainedHuggingFaceTextSummarizer': <class 'djai.model.models.ml.hugging_face.text_summarization.PreTrainedHuggingFaceTextSummarizer'>, 'PreTrainedHuggingFaceTokenClassifier': <class 'djai.model.models.ml.hugging_face.token_classification.PreTrainedHuggingFaceTokenClassifier'>, 'PreTrainedHuggingFaceTransformer': <class 'djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer'>, 'PreTrainedHuggingFaceTranslator': <class 'djai.model.models.ml.hugging_face.translation.PreTrainedHuggingFaceTranslator'>, 'PreTrainedHuggingFaceZeroShotClassifier': <class 'djai.model.models.ml.hugging_face.zero_shot_classification.PreTrainedHuggingFaceZeroShotClassifier'>, 'PreTrainedKerasImageNetClassifier': <class 'djai.model.models.ml.keras.pre_trained.vision.image_classification.PreTrainedKerasImageNetClassifier'>, 'SKLModel': <class 'djai.model.models.ml.skl.SKLModel'>, 'TorchModel': <class 'djai.model.models.ml.torch.base.TorchModel'>, '_AIModelWithArtifactFilesABC': <class 'djai.model.models.base._AIModelWithArtifactFilesABC'>, '_PreTrainedMLModelABC': <class 'djai.model.models.ml.base._PreTrainedMLModelABC'>}

uuid: UUIDField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

class djai.model.models.CloudAIService(*args, **kwargs)

Bases: djai.model.models.base.AIModel

DjAI Cloud AI Service model class.

exception DoesNotExist

Bases: djai.model.models.base.AIModel.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.base.AIModel.MultipleObjectsReturned

aimodel_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

aimodel_ptr_id

google_translate

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

class djai.model.models.GoogleTranslate(*args, **kwargs)

Bases: djai.model.models.cloud_ai_svc.base.CloudAIService

Google Translate Service.

exception DoesNotExist

Bases: djai.model.models.cloud_ai_svc.base.CloudAIService.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.cloud_ai_svc.base.CloudAIService.MultipleObjectsReturned

client = None

cloudaiservice_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

cloudaiservice_ptr_id

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Textbox(label="Text to Translate") |-Dropdown(label="Source Language") |-Dropdown(label="Destination Language") outputs: |-Textbox(label="Translated Text")

load() → None

Load Google Translate Client.

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(text_or_texts: Union[str, collections.abc.Sequence[str]], src: str = 'auto', dest: str = 'en') → Union[str, List[str]]

Translate.

class djai.model.models.KerasModel(*args, **kwargs)

Bases: djai.model.models.base._AIModelWithArtifactFilesABC

DjAI TensorFlow.Keras Deep Learning Model class.

class Meta

Bases: djai.model.models.base._AIModelWithArtifactFilesABC.Meta

Django Model Class Metadata.

abstract = False

aimodel_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

aimodel_ptr_id

artifact_global_url: django.db.models.fields.CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

artifact_local_path: django.db.models.fields.CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

load() → None

Load the Model’s native object from it artifact file.

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

class djai.model.models.PreTrainedHuggingFaceAudioClassifier(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Audio Classifier Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: _predict ------------------------------ inputs: |-Audio(label="Audio to Classify") |-Slider(label="No. of Labels to Return") outputs: |-Label(label="Audio Classification")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(audio_or_audios: Union[numpy.ndarray, str, collections.abc.Sequence[Union[numpy.ndarray, str]]], n_labels: int = 5) → Union[Dict[str, float], List[Dict[str, float]]]

Classify Audio(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceImageClassifier(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Image Classifier Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Image(label="Upload an Image to Classify") |-Slider(label="No. of Labels to Return") outputs: |-Label(label="Likely ImageNet Classes")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(image_or_images: Union[str, PIL.Image.Image, collections.abc.Sequence[Union[str, PIL.Image.Image]]], n_labels: int = 5) → Union[Dict[str, float], List[Dict[str, float]]]

Classify Image(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceMaskFiller(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Mask Filler Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: _predict ------------------------------ inputs: |-Textbox(label="Text to Generate from") |-Dataframe(label="Targets") |-Slider(label="No. of Labels to Return") outputs: |-Label(label="Generated Text")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(text_or_texts: Union[str, collections.abc.Sequence[str]], targets: Optional[List[str]] = None, n_labels: int = 5) → Union[Dict[str, float], List[Dict[str, float]]]

Classify Image(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceObjectDetector(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Object Detector Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: _predict ------------------------------ inputs: |-Image(label="Upload an Image to Detect Objects") |-Slider(label="Confidence Threshold") outputs: |-Image(label="Detected Objects") |-JSON(label="Detected Objects")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(image_or_images: Union[str, PIL.Image.Image, collections.abc.Sequence[Union[str, PIL.Image.Image]]], threshold: float = 0.9) → Union[List[dict], collections.abc.Sequence[List[dict]]]

Detect Objects from Image(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceQuestionAnswerer(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Question Answerer Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: <lambda> ------------------------------ inputs: |-Textbox(label="Question") |-Textbox(label="Context") |-Number(label="Top K") |-Number(label="Doc Stride") |-Number(label="Max Answer Length") |-Number(label="Max Sequence Length") |-Number(label="Max Question Length") |-Checkbox(label="Handle Impossible Answer?") outputs: |-JSON(label="Likely Answer(s)")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(question: Union[str, collections.abc.Sequence[str]], context: Union[str, collections.abc.Sequence[str]], top_k: int = 1, doc_stride: int = 128, max_answer_len: int = 15, max_seq_len: int = 384, max_question_len: int = 64, handle_impossible_answer: bool = False) → Union[dict, List[dict]]

Answer Question(s) based on Text(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceSpeechRecognizer(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Speech Recognizer Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: _predict ------------------------------ inputs: |-Audio(label="Recorded Speech to Transcribe") outputs: |-Textbox(label="Transcribed Text")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(speech_or_speeches: Union[numpy.ndarray, str, collections.abc.Sequence[Union[numpy.ndarray, str]]]) → Union[str, List[str]]

Recognize Speech(es).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceTableQuestionAnswerer(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Table Question Answerer Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Dataframe(label="Data Table") |-Textbox(label="Query") |-Checkbox(label="Sequential?") |-Checkbox(label="Padding?") |-Checkbox(label="Truncation?") outputs: |-JSON(label="Likely Answer(s)")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(table: Union[dict, pandas.core.frame.DataFrame], queries: Union[str, collections.abc.Sequence[str]], sequential: bool = False, padding: Union[bool, str] = False, truncation: Union[bool, str] = False) → Union[dict, List[dict]]

Answer Question(s) on a Tabular Data Set.

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceText2TextGenerator(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Text-to-Text Generator Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Textbox(label="Text to Generate from") |-Checkbox(label="Return Tensors?") |-Checkbox(label="Return Text?") outputs: |-JSON(label="Generated Text")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(text_or_texts: Union[str, collections.abc.Sequence[str]], return_tensors: bool = False, return_text: bool = True, clean_up_tokenization_spaces: bool = True, **generate_kwargs) → Union[str, List[int], List[Union[str, List[int]]]]

Generate Text-to-Text.

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceTextClassifier(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Text Classifier Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Textbox(label="Text to Classify") outputs: |-Label(label="Likely Text Classes")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(text_or_texts: Union[str, collections.abc.Sequence[str]]) → Union[Dict[str, float], collections.abc.Sequence[Dict[str, float]]]

Classify Text(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceTextGenerator(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Text Generator Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Textbox(label="Text to Generate from") |-Checkbox(label="Return Tensors?") |-Checkbox(label="Return Text?") |-Checkbox(label="Return Full Text?") |-Checkbox(label="Clean Up Spaces?") |-Textbox(label="Generated Text Prefix") outputs: |-JSON(label="Generated Text")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(text_or_texts: Union[str, collections.abc.Sequence[str]], return_tensors: bool = False, return_text: bool = True, return_full_text: bool = True, clean_up_tokenization_spaces: bool = True, prefix: Optional[str] = None, **generate_kwargs) → Union[str, List[int], List[Union[str, List[int]]]]

Generate Text(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceTextSummarizer(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Text Summarizer Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Textbox(label="Text to Summarize") |-Checkbox(label="Return Text?") |-Checkbox(label="Return Tensors?") |-Checkbox(label="Clean Up Spaces?") outputs: |-JSON(label="Summary Text")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(text_or_texts: Union[str, collections.abc.Sequence[str]], return_text: bool = True, return_tensors: bool = False, clean_up_tokenization_spaces: bool = True, **generate_kwargs) → Union[str, List[int], List[Union[str, List[int]]]]

Summarize Text(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceTokenClassifier(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Token Classifier Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Textbox(label="Text from which to Recognize Tokens") outputs: |-JSON(label="Recognized Tokens")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(text_or_texts: Union[str, collections.abc.Sequence[str]]) → Union[List[dict], collections.abc.Sequence[List[dict]]]

Classify Tokens in Text(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceTransformer(*args, **kwargs)

Bases: djai.model.models.ml.base._PreTrainedMLModelABC

DjAI Pre-Trained Hugging Face Transformer Model class.

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

aimodel_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

aimodel_ptr_id

artifact_global_url: CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

artifact_local_path: CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

loader_module_and_qualname: django.db.models.fields.CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

pretrained_hugging_face_audio_classifiers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_image_classifiers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_mask_fillers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_object_detectors

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_question_answerers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_speech_recognizers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_table_question_answerers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_text2text_generators

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_text_classifiers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_text_generators

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_text_summarizers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_token_classifiers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_translators

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

pretrained_hugging_face_zero_shot_classifiers

Accessor to the related object on the reverse side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Place.restaurant is a ReverseOneToOneDescriptor instance.

class djai.model.models.PreTrainedHuggingFaceTranslator(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Translator Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Textbox(label="Text to Summarize") |-Checkbox(label="Return Tensors?") |-Checkbox(label="Return Text?") |-Checkbox(label="Clean Up Spaces?") |-Dropdown(label="Source Language") |-Dropdown(label="Target Language") outputs: |-JSON(label="Translated Text")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(text_or_texts: Union[str, collections.abc.Sequence[str]], return_tensors: bool = False, return_text: bool = True, clean_up_tokenization_spaces: bool = True, src_lang: Optional[str] = None, tgt_lang: Optional[str] = None, **generate_kwargs) → Union[str, List[int], List[Union[str, List[int]]]]

Translate Text(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedHuggingFaceZeroShotClassifier(*args, **kwargs)

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer

DjAI Pre-Trained Hugging Face Zero-Shot Classifier Model class.

exception DoesNotExist

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.DoesNotExist

exception MultipleObjectsReturned

Bases: djai.model.models.ml.hugging_face.base.PreTrainedHuggingFaceTransformer.MultipleObjectsReturned

gradio_ui = Gradio Interface for: <lambda> ------------------------------ inputs: |-Textbox(label="Text to Classify") |-Dataframe(label="Candidate Labels") |-Textbox(label="Hypothesis Format") |-Checkbox(label="Multi-Label?") outputs: |-Label(label="Label Probabilities")

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(text_or_texts: Union[str, collections.abc.Sequence[str]], candidate_labels: List[str], hypothesis_template: str = 'This example is {}.', multi_label: bool = False) → Union[Dict[str, float], List[Dict[str, float]]]

Zero-Shot Classification of Text(s).

pretrainedhuggingfacetransformer_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

pretrainedhuggingfacetransformer_ptr_id

class djai.model.models.PreTrainedKerasImageNetClassifier(*args, **kwargs)

Bases: djai.model.models.ml.base._PreTrainedMLModelABC

DjAI Pre-Trained Keras Image Classification Model class.

exception DoesNotExist

Bases: django.core.exceptions.ObjectDoesNotExist

exception MultipleObjectsReturned

Bases: django.core.exceptions.MultipleObjectsReturned

aimodel_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

aimodel_ptr_id

artifact_global_url: CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

artifact_local_path: CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

gradio_ui = Gradio Interface for: predict ----------------------------- inputs: |-Image(label="Upload an Image to Classify") |-Slider(label="No. of ImageNet Labels to Return") outputs: |-Label(label="Likely ImageNet Labels")

property img_dim_size: int

(Square) Image Dimension Size.

loader_module_and_qualname: CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

predict(image_or_images: Union[str, _io.BytesIO, PIL.Image.Image, numpy.ndarray, collections.abc.Sequence[Union[str, _io.BytesIO, PIL.Image.Image, numpy.ndarray]]], n_labels: int = 5) → Union[Dict[str, float], List[Dict[str, float]]]

Classify Image(s).

property preprocessor: callable

Image Preprocessor method.

preprocessor_module_and_qualname: django.db.models.fields.CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

class djai.model.models.SKLModel(*args, **kwargs)

Bases: djai.model.models.base._AIModelWithArtifactFilesABC

DjAI SciKit-Learn Machine Learning Model class.

class Meta

Bases: djai.model.models.base._AIModelWithArtifactFilesABC.Meta

Django Model Class Metadata.

abstract = False

aimodel_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

aimodel_ptr_id

artifact_global_url: django.db.models.fields.CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

artifact_local_path: django.db.models.fields.CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

load() → None

Load the Model’s native object from it artifact file.

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

save(*args, **kwargs)

Save the Model into the DB, and its native object into file.

class djai.model.models.TorchModel(*args, **kwargs)

Bases: djai.model.models.base._AIModelWithArtifactFilesABC

DjAI Torch Deep Learning Model class.

class Meta

Bases: djai.model.models.base._AIModelWithArtifactFilesABC.Meta

Django Model Class Metadata.

abstract = False

aimodel_ptr

Accessor to the related object on the forward side of a one-to-one relation.

In the example:

class Restaurant(Model):
    place = OneToOneField(Place, related_name='restaurant')

Restaurant.place is a ForwardOneToOneDescriptor instance.

aimodel_ptr_id

artifact_global_url: django.db.models.fields.CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

artifact_local_path: django.db.models.fields.CharField

A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.

load() → None

Load the Model’s native object from it artifact file.

polymorphic_primary_key_name = 'uuid'

polymorphic_super_sub_accessors_replaced = False

Subpackages

• djai.model.models.cloud_ai_svc package
  • Subpackages
    • djai.model.models.cloud_ai_svc.amazon package
    • djai.model.models.cloud_ai_svc.google package
      • Submodules
    • djai.model.models.cloud_ai_svc.hugging_face package
    • djai.model.models.cloud_ai_svc.ibm_watson package
    • djai.model.models.cloud_ai_svc.meta package
    • djai.model.models.cloud_ai_svc.microsoft package
    • djai.model.models.cloud_ai_svc.wolfram_alpha package
  • Submodules
    • djai.model.models.cloud_ai_svc.base module
• djai.model.models.ml package
  • Subpackages
    • djai.model.models.ml.hugging_face package
      • Submodules
    • djai.model.models.ml.keras package
      • Subpackages
      • Submodules
    • djai.model.models.ml.torch package
      • Subpackages
      • Submodules
  • Submodules
    • djai.model.models.ml.base module
    • djai.model.models.ml.skl module

Submodules

• djai.model.models.base module