EleutherAI
How do large language models (LLMs) develop and evolve over the course of training? How do these patterns change as models scale? To answer these questions, we introduce \textit{Pythia}, a suite of 16 LLMs all trained on public data seen in the exact same order and ranging in size from 70M to 12B parameters.
Running this yourself: consumer gpu should be enough.
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Quality Score
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Arena ELO
7B
Parameters
2K
Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
14 of 22 public signals
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668.8K
Downloads
66
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Feb 2023
Released
5/5 signals
0/4 signals
3/5 signals
3/4 signals
3/4 signals
Parameters
7B
Training compute
1.2e22 FLOP
Dataset scale
299.9B units
Base model
Not reported
Source-reported access: Open weights (unrestricted) · Confident confidence
Gaps we are still tracking