Settings API Reference Bumblebee v0.1.2

Pre-trained Axon models for easy inference and boosted training.

An interface for configurable entities.

Denoising diffusion implicit models (DDIMs).

Pseudo numerical methods for diffusion models (PNDMs).

High-level tasks based on Stable Diffusion.

A CLIP-based model for detecting unsafe image content.

U-Net model with two spatial dimensions and conditional state.

Variational autoencoder (VAE) with Kullback–Leibler divergence (KL) loss.

An interface for configuring and applying featurizers.

An interface for configuring and building models based on the same architecture.

The CLIP model for text-image similarity.

LayoutLM Model family.

An interface for configuring and using schedulers.

High-level tasks related to text processing.

ALBERT model family.

ALBERT tokenizer.

BART model family.

BART tokenizer.

BERT model family.

BERT tokenizer.

The CLIP model for text encoding.

CLIP tokenizer.

An interface for language models supporting sequence generation.

GPT-2 model family.

GPT-2 tokenizer.

LayoutLM tokenizer.

mBART model family.

mBART tokenizer.

RoBERTa model family.

RoBERTa tokenizer.

An interface for configuring and applying tokenizers.

High-level tasks related to vision.

CLIP featurizer for image data.

The CLIP model for image encoding.

ConvNeXT model family.

ConvNeXT featurizer for image data.

DeiT model family.

DeiT featurizer for image data.

ResNet model family.

ViT model family.

ViT featurizer for image data.