metadata

library_name: transformers
license: apache-2.0
datasets:
  - grascii/gregg-preanniversary-words
pipeline_tag: image-to-text

Gregg Vision v0.2.1

Gregg Vision v0.2.1 generates a Grascii representation of a Gregg Shorthand form.

Model type: Vision Encoder Text Decoder
License: Apache 2.0
Repository: [More Information Needed]
Demo: Grascii Search Space

Uses

Given a grayscale image of a single shorthand form, Gregg Vision can be used to generate its Grascii representation. When combined with Grascii Search, one can obtain possible English interpretations of the shorthand form.

How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

Technical Details

Model Architecture and Objective

Gregg Vision v0.2.1 is a transformer model with a ViT encoder and a Roberta decoder.

For training, the model was warm-started using vit-small-patch16-224-single-channel for the encoder and a randomly initialized Roberta network for the decoder.

Training Data

Gregg Vision v0.2.1 was trained on the gregg-preanniversary-words dataset.

Training Hardware

Gregg Vision v0.2.1 was trained using 1xT4.