opt-2.7b

Maintained By
facebook

OPT-2.7B

PropertyValue
DeveloperMeta AI (Facebook)
ArchitectureDecoder-only Transformer
LicenseOther (Custom)
PaperOpen Pre-trained Transformer Language Models

What is opt-2.7b?

OPT-2.7B is part of Meta AI's Open Pre-trained Transformer (OPT) series, designed to democratize access to large language models. This 2.7 billion parameter model represents a significant step in making powerful language models available for research and development, trained on a diverse dataset of 180B tokens.

Implementation Details

The model utilizes a decoder-only transformer architecture and employs the GPT-2 byte-level BPE tokenizer with a vocabulary size of 50,272. It processes sequences of up to 2048 tokens and was trained using a causal language modeling objective.

  • Trained on 800GB of diverse text data including BookCorpus, CC-Stories, and selected components of The Pile
  • Uses efficient training practices and modern architectural improvements
  • Implements top-k sampling for varied text generation

Core Capabilities

  • Text generation and completion
  • Zero-shot and few-shot learning
  • Causal language modeling
  • Research and experimentation in NLP

Frequently Asked Questions

Q: What makes this model unique?

OPT-2.7B stands out for its open-source nature and commitment to responsible AI development. It provides researchers full model access, unlike many comparable models that are only available through APIs.

Q: What are the recommended use cases?

The model is best suited for text generation tasks, research in language model behavior, and fine-tuning for specific applications. However, users should be aware of potential biases and limitations in generated content.

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