OPT-13B
| Property | Value |
|---|---|
| Author | Meta AI (Facebook) |
| License | Other (Research Only) |
| Paper | Open Pre-trained Transformer Language Models |
| Training Data | 180B tokens (800GB) |
| Primary Use | Text Generation |
What is opt-13b?
OPT-13B is part of Meta AI's Open Pretrained Transformer (OPT) series, designed to democratize access to large language models. This 13-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 GPT2's byte-level BPE tokenization with a 50,272 vocabulary size and processes sequences of 2048 tokens. It's optimized for half-precision (float16) inference on GPU hardware and employs causal language modeling for pre-training.
- Trained on multiple high-quality datasets totaling 180B tokens
- Implements efficient training practices and modern architecture optimizations
- Supports both deterministic and sampling-based text generation
Core Capabilities
- Zero-shot and few-shot learning tasks
- Natural language generation and completion
- Research-focused experimentation and analysis
- Customizable text generation with sampling parameters
Frequently Asked Questions
Q: What makes this model unique?
OPT-13B stands out for its open-access nature, allowing researchers to study large language model behavior, while matching GPT-3-class performance. It's specifically designed for responsible AI research and comes with comprehensive documentation about its limitations and biases.
Q: What are the recommended use cases?
The model is best suited for research applications, text generation tasks, and studying language model behavior. It can be used for both direct prompting and fine-tuning on downstream tasks, though users should be aware of potential biases in the training data.
