Memory Caching SSC with 2, 4, or 8 recurrent states. All use seed 1111, 6,000 optimizer steps, a global batch of 256 at sequence length 2,048 (3,145,728,000 training tokens), and a 4× rare-recall loss weight. The tokenization is GPT-2. See manifest.json for the exact checkpoint, resolved-config, evaluator, and cohort identities. These files require the project-specific model implementation. They are not Transformers AutoModel checkpoints. The training source is The evaluation source is which preserves those model implementations and adds the named full suites. Run SWDE on all 1,111 examples and SQuAD completion on all 2,984 examples for each of the nine checkpoints. The eval/ folder…
Independent publisher
Jerry Liu
jwl50-stanford
Models in Library1
Datasets in Library0
Models on Hugging Face13
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