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2.13 kB
| license: apache-2.0 | |
| language: | |
| - en | |
| task_categories: | |
| - text-generation | |
| tags: | |
| - synthetic | |
| - datainventor | |
| size_categories: | |
| - n<1K | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train.jsonl | |
| pretty_name: "DataInventor: General customer support" | |
| # DataInventor: General customer support | |
| A synthetic instruction dataset of 200 rows in English, built with [DataInventor](https://huggingface.co/spaces/LocalLLaMA/data-inventor), an open-source recreation of the Invent a Dataset workflow. Describe the data you want and DataInventor writes it. This is one of eight showcase datasets. | |
| ## Request | |
| > A dataset of customer support inquiries and corresponding responses, covering issues such as product information, technical troubleshooting, billing disputes, and service returns. | |
| The wording is one of the eight example requests in the Invent a Dataset technical report from Adaption Labs. This dataset is not affiliated with Adaption Labs and does not contain any of their output. | |
| ## How it was made | |
| 1. A blueprint was drafted from the request: topics, who asks, who answers, and the shapes a question can take. | |
| 2. Unique combinations of topic, persona, shape, difficulty and length were sampled. | |
| 3. For each combination, one message was written, then the reply. | |
| 4. Rows were rejected for cut-off or degenerate text, for asking for many items at once, and for near-duplicate questions. | |
| Generated with optillm. | |
| ## Columns | |
| `prompt`, `completion`, plus `area`, `subtopic`, `topic`, `persona`, `shape`, `difficulty` and `language` describing how each row was planned. | |
| ## Quick numbers | |
| - Rows: 200 | |
| - Distinct 3-grams in prompts: 0.883 | |
| - Average words per prompt: 55.4 | |
| - Average words per completion: 337.4 | |
| ## Limits | |
| - Every row was written by a language model and has not been checked by a person. Replies can contain errors and invented facts. Check them before you train on this data or rely on it. | |
| - Synthetic data repeats the habits and blind spots of the model that wrote it. | |
| Make your own with [DataInventor](https://huggingface.co/spaces/LocalLLaMA/data-inventor). License: Apache 2.0. | |