Imagine auto-regressive generation to be 90x faster. tf-transformers (Tensorflow Transformers) is designed to harness the full power of Tensorflow 2, designed specifically for Transformer based architecture. These models can be applied on text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages. Images, for tasks like image classification, object detection, and segmentation. Audio, for tasks like speech recognition and audio classification. Faster AutoReggressive Decoding, TFlite support, creating TFRecords is simple. Auto-Batching tf.data.dataset or tf.ragged tensors. Everything is dictionary (inputs and outputs) Multiple mask modes like causal, user-defined, prefix. tensorflow-text tokenizer support. Supports GPU, TPU, multi-GPU trainer with wandb, multiple callbacks, auto tensorboard.
Features
- TFlite support
- Auto-Batching tf.data.dataset or tf.ragged tensors
- Everything is dictionary (inputs and outputs)
- tensorflow-text tokenizer support
- Multiple mask modes like causal, user-defined, prefix
- Supports GPU, TPU, multi-GPU trainer with wandb, multiple callbacks, auto tensorboard
Project Samples
