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FAST: Efficient Action Tokenization for Vision-Language-Action Models - AI Robotics Tool

Overview

FAST (FAST+) provides a universal action tokenizer that maps robot action sequences into dense, discrete tokens for training autoregressive vision-language-action (VLA) models. The Hugging Face repository includes a pre-trained tokenizer and tools to train custom tokenizers on your own robot action datasets.

Key Features

  • FAST+ universal action tokenizer mapping robot action sequences to dense discrete tokens
  • Designed for training autoregressive vision-language-action (VLA) models
  • Includes a pre-trained tokenizer for immediate experimentation
  • Supports easy custom tokenizer training on users' datasets
  • Repository hosted on Hugging Face for code and model access

Ideal Use Cases

  • Tokenize robot action datasets for model training
  • Preprocess actions for autoregressive VLA model pipelines
  • Fine-tune or adapt tokenizers to custom robot hardware
  • Prototype sequence-level behavior prediction and generation

Getting Started

  • Open the repository on Hugging Face
  • Read the README and usage examples
  • Install listed dependencies and required packages
  • Run example scripts using the pre-trained tokenizer
  • Train a custom tokenizer on your action dataset if needed
  • Integrate tokens into your VLA model training pipeline

Pricing

No pricing or commercial terms disclosed in the repository metadata. Check the Hugging Face repository or maintainers for licensing and usage details.

Limitations

  • Code repository, not a hosted robot control service
  • Requires dataset preparation and model training for usable tokenizers
  • May require machine learning and robotics expertise to integrate

Key Information

  • Category: Robotics
  • Type: AI Robotics Tool
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