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evalstate
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evalstate
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From an exploratory tiny-scale replication of How much do language models memorize?.
This is the near-capacity (saturation-boundary) run for this model size.
Below- and above-capacity checkpoints for the same architecture are published as
state.pt files in the results dataset evalstate/tiny-memorization-results.
Load with:
python
from transformers import GPT2LMHeadModelmodel = GPT2LMHeadModel.from_pretrained("evalstate/tiny-gpt-memorization-2m")
Findings are scoped as an exploratory tiny-scale check (three architectures), NOT a universal scaling law.