Pythia-1B
| Property | Value |
|---|---|
| Parameter Count | 1.08B parameters |
| License | Apache 2.0 |
| Architecture | GPT-NeoX |
| Paper | Research Paper |
| Training Data | The Pile |
What is pythia-1b?
Pythia-1B is a 1.08 billion parameter language model that belongs to the Pythia Scaling Suite developed by EleutherAI. This model is specifically designed for research purposes, particularly in the field of AI interpretability. It features 16 layers with a model dimension of 2048 and 8 attention heads, trained on The Pile dataset.
Implementation Details
The model is implemented using the GPT-NeoX architecture and trained with a batch size of 2M tokens. It utilizes Flash Attention and implements a learning rate schedule that decays to 10% of the starting rate. The model provides 154 checkpoints throughout its training process, enabling researchers to study its learning progression.
- Training Dataset: The Pile (825GiB English dataset)
- Architecture: 16 layers, 2048 model dimension, 8 attention heads
- Training Steps: 143,000 with 2M token batch size
- Compatible with Hugging Face Transformers Library
Core Capabilities
- Next-token prediction for English text generation
- Research-focused capabilities for interpretability studies
- Checkpoint analysis through 154 saved states
- Comparable performance to similar-sized models like GPT-Neo
Frequently Asked Questions
Q: What makes this model unique?
Pythia-1B is part of a carefully designed research suite with consistent training conditions and extensive checkpointing, making it ideal for studying model behavior and interpretability. Unlike products like ChatGPT, it's not fine-tuned for specific downstream tasks.
Q: What are the recommended use cases?
The model is primarily intended for research on language model behavior and limitations. It's not recommended for deployment in production environments or human-facing applications without appropriate fine-tuning and safety considerations.
