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+ }
README.md ADDED
@@ -0,0 +1,113 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language:
3
+ - en
4
+ license: apache-2.0
5
+ tags:
6
+ - synthetic
7
+ - pretraining
8
+ - text-generation
9
+ - language-modeling
10
+ task_categories:
11
+ - text-generation
12
+ task_ids:
13
+ - language-modeling
14
+ size_categories:
15
+ - 1M<n<10M
16
+ pretty_name: SYN-1B
17
+ configs:
18
+ - config_name: default
19
+ data_files:
20
+ - split: train
21
+ path: data/train-*.parquet
22
+ - split: validation
23
+ path: data/validation-*.parquet
24
+ train-eval-index:
25
+ - config: default
26
+ task: text-generation
27
+ task_id: language-modeling
28
+ splits:
29
+ train_split: train
30
+ eval_split: validation
31
+ col_mapping:
32
+ text: text
33
+ ---
34
+
35
+ # Dataset Card for SYN-1B
36
+
37
+ Repository: https://github.com/QuixiAI/AUM
38
+
39
+ ## Dataset Summary
40
+
41
+ SYN-1B is the AUM synthetic task corpus generated from the local `syn-1b-v1.3`
42
+ specification. The Parquet files expose one decoded synthetic instance per row in
43
+ the `text` column. The original packed `uint16` token shards, sidecars, and QA
44
+ manifests remain in this directory for exact token-level training and audit use.
45
+
46
+ The Hugging Face `validation` split corresponds to the SYN generator's `eval`
47
+ split. F5 appears only in that held-out eval/validation split.
48
+
49
+ ## Purpose
50
+
51
+ SYN-1B exists to test the central claim in AUM-Ø: a model should separate
52
+ evidence from interpretation, then spend extra computation only when revising
53
+ the interpretation is useful. AUM-Ø maintains an evidence state that records
54
+ what has been observed and a compact hypothesis register that tracks how that
55
+ evidence should currently be interpreted. The synthetic corpus provides
56
+ programmatic tasks with known latent hypotheses so the training and evaluation
57
+ harness can ask whether the register actually tracks the active rule, whether
58
+ silent revision helps at sparse interpretive events, and whether pressure is
59
+ allocated where counterfactual benefit predicts it will pay.
60
+
61
+ As described in `AUM-Ø.md`, the broader pretraining recipe mixes filtered
62
+ web/education text, code, and a 5% stream of synthetic structured tasks. That
63
+ synthetic fraction is not filler: the sigma-decode probe, recency falsifier,
64
+ flat-null control, and evidence-age measurements are computed on it. SYN-1B is
65
+ the corpus-scale version of those tasks in the real 49,152-token SmolLM2 BPE
66
+ space, as specified in `SYN-1B.md`.
67
+
68
+ The task families are designed to isolate different parts of the mechanism:
69
+
70
+ | Family | Role |
71
+ | --- | --- |
72
+ | F1 branch reversal | A rule holds, then an event changes the active mapping. |
73
+ | F2 binding swap | Entity-to-attribute bindings are corrected by swaps rather than a single surface marker. |
74
+ | F3 delayed correction / recall | Old evidence and controlled evidence age test whether stored evidence survives and can be reinterpreted. |
75
+ | F4 flat null | No interpretive event occurs, so pressure and silent depth should stay near zero. |
76
+ | F5 modular-stream switch | Eval-only transfer task with no training exposure, used to test whether probes generalize beyond memorized formats. |
77
+
78
+ This local Hugging Face view is a convenience format. The raw packed token
79
+ stream and sidecars are the authoritative artifact for mechanism probes,
80
+ token-level QA, and exact reproduction of the SYN-1B build.
81
+
82
+ ## How to Load
83
+
84
+ ```python
85
+ from datasets import load_dataset
86
+
87
+ ds = load_dataset("/home/hotaisle/datasets/SYN-1B")
88
+ ```
89
+
90
+ ## Dataset Stats
91
+
92
+ | Split | Rows | Synthetic instance tokens |
93
+ | --- | ---: | ---: |
94
+ | `train` | 4,046,772 | 1,000,002,097 |
95
+ | `validation` | 178,463 | 40,002,369 |
96
+ | `total` | 4,225,235 | 1,040,004,466 |
97
+
98
+ Tokenizer: `HuggingFaceTB/SmolLM2-135M`
99
+
100
+ ## Data Schema
101
+
102
+ Columns:
103
+
104
+ - `text`: decoded synthetic instance text.
105
+ - `instance_id`, `family`, `syn_split`: stable identifiers and SYN family.
106
+ - `token_len`, `task_token_count`, `filler_token_count`, `controlled_gap_tokens`,
107
+ `composition_depth`, `num_queries`: compact per-instance metadata.
108
+ - `shard`, `window_index`, `start_offset`, `token_hash`: join keys back to the
109
+ packed raw token stream and sidecar records.
110
+
111
+ ## Licensing Information
112
+
113
+ License: Apache-2.0
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