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| license: cc-by-4.0 | |
| language: | |
| - en | |
| - fr | |
| pretty_name: skycmd zero-shot intent sets | |
| task_categories: | |
| - text-classification | |
| tags: | |
| - skycmd | |
| - typed-decisions | |
| - system-one | |
| configs: | |
| - config_name: zs_banking77 | |
| data_files: data/zs_banking77.parquet | |
| - config_name: zs_massive_en | |
| data_files: data/zs_massive_en.parquet | |
| - config_name: zs_massive_fr | |
| data_files: data/zs_massive_fr.parquet | |
| # skycmd zero-shot intent sets | |
| The zero-shot test sets of the s4 and s6 models: MASSIVE intents in English (2,000) and French (1,000) and Banking77 (2,000) as typed choice questions over intents. | |
| Part of [skycmd](https://github.com/maxgfr/skycmd), tiny decision models trained from scratch in Rust that run in the | |
| browser. Written by `sky-data s4-corpus --only-heldout` at commit [`6cbcce8c`](https://github.com/maxgfr/skycmd/commit/6cbcce8cbbbf27e8e952e61b6cb1ed03ee1fca58). | |
| Licences of every set: [DATA_LICENSES.md](https://github.com/maxgfr/skycmd/blob/main/DATA_LICENSES.md). | |
| Each row is one typed decision question (docs/SPEC.md): | |
| | field | type | meaning | | |
| |---|---|---| | |
| | `src` | string | source | | |
| | `t` | string | `choice`, `score` or `noul` | | |
| | `ins` | string | the question | | |
| | `opts` | list of strings | the options, rendered as text | | |
| | `state` | string | the state the question is about | | |
| | `target` | list of floats | a probability per option (soft or one-hot) | | |
| | `split` | string | `train`, `val` or `test` | | |
| ## Source and licence | |
| MASSIVE (CC-BY-4.0) and PolyAI/banking77 (CC-BY-4.0). The conversion is ours. | |
| ## Files | |
| | file | rows | | |
| |---|---:| | |
| | `data/zs_banking77.parquet` | 2,000 | | |
| | `data/zs_massive_en.parquet` | 2,000 | | |
| | `data/zs_massive_fr.parquet` | 1,000 | | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("maxgfr/skycmd-zero-shot", "zs_banking77") | |
| ``` | |
| skycmd wrote no row with a language model: the targets come from the upstream labels (some upstream | |
| sets carry their own teacher soft labels, see their cards), the games' oracles or our generators. | |