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1 Parent(s): 621e605

Fix the byte-identity claim, the placeholder dataset id and the extras description

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  1. README.md +5 -5
README.md CHANGED
@@ -53,7 +53,7 @@ dataset exists for, and it is asserted at build time.
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  ```
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  data/<config>/test-*.parquet the evaluation set, one row per case
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- extras/<config>/ the same arrays in numpy form, plus the GFP tensors
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  case_index.parquet case id, edge id, label, typology, HT weight
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  ml_baselines/weights/ all three ensemble members, 5 seeds each
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  ml_baselines/test_probs/ full-test-split probabilities for the 3 ensemble members
@@ -73,13 +73,13 @@ ml_baselines/test_probs/ full-test-split probabilities for the 3 ensemble
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  | `ht_weight` | float64 | Horvitz-Thompson importance weight. Apply when aggregating P, R and F1. |
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  | `n_transactions` | int32 | Transactions in the two-hop subgraph. |
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  | `n_tokens_approx` | int32 | Approximate prompt length. |
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- | `typed_graph_text` | string | The typed-graph prompt, byte-identical to what the evaluated models were given. |
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  ## Usage
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  ```python
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  from datasets import load_dataset
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- ds = load_dataset("<org>/amlcompact", "HI-Small", split="test")
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  print(ds[0]["case_id"], ds[0]["label"], ds[0]["typology"])
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  print(ds[0]["typed_graph_text"][:200])
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  ```
@@ -146,8 +146,8 @@ genuinely null. Rows are in `case_id` order, which is the join key against the r
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  predictions and the rubric annotations, so the file is deliberately not sorted to put labelled
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  rows first.
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- To browse labels and weights without pulling the prompt column, use `extras/<config>/`, which
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- carries the same arrays in numpy form at 1.6 MB total.
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  ## Case identifiers
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  ```
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  data/<config>/test-*.parquet the evaluation set, one row per case
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+ extras/<config>/ the same arrays as .npy, plus the GFP tensors
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  case_index.parquet case id, edge id, label, typology, HT weight
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  ml_baselines/weights/ all three ensemble members, 5 seeds each
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  ml_baselines/test_probs/ full-test-split probabilities for the 3 ensemble members
 
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  | `ht_weight` | float64 | Horvitz-Thompson importance weight. Apply when aggregating P, R and F1. |
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  | `n_transactions` | int32 | Transactions in the two-hop subgraph. |
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  | `n_tokens_approx` | int32 | Approximate prompt length. |
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+ | `typed_graph_text` | string | The typed-graph prompt the evaluated models were given, identical except for the case identifier token (see Case identifiers). |
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  ## Usage
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  ```python
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  from datasets import load_dataset
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+ ds = load_dataset("natnitaract/amlcompact-eval", "HI-Small", split="test")
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  print(ds[0]["case_id"], ds[0]["label"], ds[0]["typology"])
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  print(ds[0]["typed_graph_text"][:200])
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  ```
 
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  predictions and the rubric annotations, so the file is deliberately not sorted to put labelled
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  rows first.
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+ To browse labels and weights without pulling the prompt column, use `extras/<config>/`: the
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+ same arrays as `.npy`, plus `case_index.parquet` as a join table, 1.5 MB in total.
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  ## Case identifiers
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