OPT-1.3B
| Property | Value |
|---|---|
| Developer | Meta AI (Facebook) |
| License | Custom (Other) |
| Paper | Open Pre-trained Transformer Language Models |
| Training Data | 180B tokens (800GB) |
What is opt-1.3b?
OPT-1.3B is part of Meta AI's Open Pre-trained Transformer (OPT) series, designed to democratize access to large language models. This 1.3 billion parameter model implements a decoder-only architecture similar to GPT-3, trained on a diverse dataset including BookCorpus, CC-Stories, and filtered content from The Pile.
Implementation Details
The model utilizes a GPT2-style byte-level BPE tokenizer with a vocabulary size of 50,272 tokens. It processes sequences of 2048 tokens and was trained using a causal language modeling objective. The training infrastructure leveraged A100 GPUs for efficient processing of the massive dataset.
- Decoder-only transformer architecture
- Pre-trained on 800GB of filtered text data
- Supports both deterministic and top-k sampling generation
- Implements efficient training practices for optimal performance
Core Capabilities
- Text generation and completion
- Zero-shot and few-shot learning
- Language understanding and processing
- Custom prompt-based tasks
Frequently Asked Questions
Q: What makes this model unique?
OPT-1.3B stands out for its open-source nature and commitment to responsible AI research. It provides comparable capabilities to GPT-3-class models while being fully accessible to researchers studying bias, toxicity, and robustness in language models.
Q: What are the recommended use cases?
The model is best suited for text generation tasks, research purposes, and fine-tuning for specific downstream applications. It can be used directly with the Transformers pipeline for text generation or fine-tuned using the causal language modeling approach.
