Transformer-based Language Model, Causal Language Model
Use Cases
Areas:
Research
Applications:
Scientific Experiments
Primary Use Cases:
Research on behavior, functionality, and limitations of large language models
Limitations:
Not suitable for deployment, May generate harmful or offensive text, English-language only, Not suitable for translation or generating text in other languages
Considerations:
Intended for a controlled research environment to study large language models.
Additional Notes
Pythia models matched or exceeded performance of similar models despite not focusing on downstream performance.
Supported Languages
en (high proficiency)
Training Details
Data Sources:
The Pile
Data Volume:
825 GiB
Methodology:
Uniform batch size with 143 checkpoints, trained on same data order
Model Architecture:
Transformer-based
Input Output
Input Format:
Plain text input through tokenization
Accepted Modalities:
text
Output Format:
Text token predictions
Performance Tips:
Ensure proper allocation of computational resources for large model sizes.
Release Notes
Version:
Current release
Date:
January 2023
Notes:
Model renamed in January 2023 as part of release changes.
Note: green Score (e.g. "73.2") means that the model is better than EleutherAI/pythia-1b.
Rank the Pythia 1B Capabilities
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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation
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