Datasets:
Simplify fixed proposals and remove cached combination scores
Browse files- README.md +2 -3
- manifest.json +4 -8
- research-assets.tar.gz +2 -2
- triplet_scores.npz +0 -3
README.md
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@@ -17,10 +17,9 @@ The matching checkpoints are in [alien-models](https://huggingface.co/alejandroh
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- `data.tar.gz`: SQLite paper and author metadata, original token vocabulary, and coherence train/validation splits. Extracts to `data/`.
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- `availability-compact.tar.gz`: the corrected availability dataset used by the released dual encoder. Extracts to `data/availability_dataset/`; approximately 1.8 GB compressed and 4.3 GB extracted.
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- `contrastive_availability_train.jsonl.gz` and `contrastive_availability_val.jsonl.gz`: optional exchange-format examples, approximately 3.75 GB and 0.42 GB compressed. The metadata and token mapping are provided alongside them.
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- `research-assets.tar.gz`: optional original selection metadata and available decoded proposals, kept separate from the updated numerical top-300 selection. See its README for coverage.
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The code README provides extraction and training commands. The compact representation is recommended for retraining.
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```bash
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hf download alejandrohdez/alien-data papers.tar.gz data.tar.gz --repo-type dataset --local-dir downloads
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- `data.tar.gz`: SQLite paper and author metadata, original token vocabulary, and coherence train/validation splits. Extracts to `data/`.
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- `availability-compact.tar.gz`: the corrected availability dataset used by the released dual encoder. Extracts to `data/availability_dataset/`; approximately 1.8 GB compressed and 4.3 GB extracted.
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- `contrastive_availability_train.jsonl.gz` and `contrastive_availability_val.jsonl.gz`: optional exchange-format examples, approximately 3.75 GB and 0.42 GB compressed. The metadata and token mapping are provided alongside them.
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- `research-assets.tar.gz`: fixed atom combinations and Markdown proposal texts from Alien (299), Random (300), Claude Opus 4.7 (300), and Gemini 3.1 Pro (300). Each method folder contains a `combinations.json` index linking atom IDs to proposal files.
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Download only the files needed for your workflow. The code README provides extraction and training commands. The compact representation is recommended for retraining.
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```bash
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hf download alejandrohdez/alien-data papers.tar.gz data.tar.gz --repo-type dataset --local-dir downloads
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manifest.json
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"availability-compact.tar.gz": {
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"bytes": 1806072602,
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research-assets.tar.gz
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triplet_scores.npz
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