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01SolidSnake123 /nanochat-depo-capability-data Nanochat Depo Capability Pilot This dataset is a deterministic natural-language rendering of the Depo directed-cycle successor task. Each row contains shuffled operational records, one exact multi-hop question, and its answer. Latent worlds are generated programmatically; no rows were written or labeled by a language model. Splits Split Worlds Queries per world Rows Renderer family train 32,768 4 131,072 incident handoff, six structural styles… See the full description on the dataset page: https://huggingface.co/datasets/SolidSnake123/nanochat-depo-capability-data.tabularquestion-answering100K<n<1M0 likes70 downloads3mo agoHugging Face02SolidSnake123 /nanochat-depo-retrieval-copy1-20260715 Nanochat Depo retrieval v1 Each latent 16-node graph yields eight independent, token-aligned, depth-one query documents. This arm exposes 1 nested edge(s) per document. Only the answer is supervised in every document; the terminal token is supervised only for query ordinal 7. This source is separate from and does not alter Depo-L0 v1. tabularquestion-answering10K<n<100K0 likes32 downloads2mo agoHugging Face03SolidSnake123 /nanochat-depo-composition-depth2-w4-retry-20260715 Nanochat Depo composition v1 Each 16-node single-cycle graph yields eight independent one-query documents: four base starts paired across query depths (1, 2). This source contains train and validation splits only. Phase depth is 2; the materialized context width is 4. tabularquestion-answering10K<n<100K0 likes25 downloads2mo agoHugging Face04SolidSnake123 /nanochat-depo-l0-symbolic-20260715 Nanochat Depo-L0: symbolic This is a diagnostic, separately versioned Depo source. Each row contains one 16-node cycle and eight queries at depths 1, 2, 4, and 8. Only the eight single-letter answers and terminal token are supervised. It is designed for a one-document-per-sequence training protocol and must not be treated as public Depo v3 data. tabularquestion-answering1K<n<10K0 likes20 downloads2mo agoHugging Face05SolidSnake123 /nanochat-depo-composition-depth2-w4-pubfix-20260715 Nanochat Depo composition v1 Each 16-node single-cycle graph yields eight independent one-query documents: four base starts paired across query depths (1, 2). This source contains train and validation splits only. Phase depth is 2; the materialized context width is 4. question-answering0 likes14 downloads2mo agoHugging Face06SolidSnake123 /nanochat-depo-composition-depth2-w4-transport-20260715 Nanochat Depo composition v1 Each 16-node single-cycle graph yields eight independent one-query documents: four base starts paired across query depths (1, 2). This source contains train and validation splits only. Phase depth is 2; the materialized context width is 4. tabularquestion-answering10K<n<100K0 likes14 downloads2mo agoHugging Face07SolidSnake123 /nanochat-depo-l0-depth1-curriculum-20260715 Nanochat Depo-L0: symbolic This is a diagnostic, separately versioned Depo source. Each row contains one 16-node cycle and eight queries under the depth1_only schedule. Only the eight single-letter answers and terminal token are supervised. It is designed for a one-document-per-sequence training protocol and must not be treated as public Depo v3 data. tabularquestion-answering10K<n<100K0 likes11 downloads2mo agoHugging Face08SolidSnake123 /nanochat-depo-retrieval-width4-20260715 Nanochat Depo retrieval v1 Each latent 16-node graph yields eight independent, token-aligned, depth-one query documents. This arm exposes 4 nested edge(s) per document. Only the answer is supervised in every document; the terminal token is supervised only for query ordinal 7. This source is separate from and does not alter Depo-L0 v1. tabularquestion-answering10K<n<100K0 likes11 downloads2mo agoHugging Face09SolidSnake123 /nanochat-depo-composition-depth2-w4-20260715 Nanochat Depo composition v1 Each 16-node single-cycle graph yields eight independent one-query documents: four base starts paired across query depths (1, 2). This source contains train and validation splits only. Phase depth is 2; the materialized context width is 4. tabularquestion-answering10K<n<100K0 likes11 downloads2mo agoHugging Face

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