| --- |
| license: mit |
| pretty_name: ChillText v2 |
| task_categories: |
| - text-generation |
| language: |
| - en |
| size_categories: |
| - 100K<n<1M |
| tags: |
| - style-transfer |
| - conversational |
| - synthetic |
| - discord |
| - imessage |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: chilltext-v2.jsonl |
| --- |
| |
| # ChillText v2 |
|
|
| ChillText v2 is a 200,000-example synthetic style-transfer dataset for making an |
| assistant's existing answer sound like a real, current Discord or iMessage reply without |
| changing its meaning. It adds the original user message as context, optional natural-language |
| personality control, strict preservation of links and identifiers, and four times as many rows |
| as [ChillText v1](https://huggingface.co/datasets/ProCreations/chilltext). |
|
|
| ## Format |
|
|
| ```json |
| {"system":"","input":"the user's actual question","agentOutput":"the assistant's normal answer","output":"casual message 1\n\ncasual message 2","n_msgs":2,"batch_id":123} |
| ``` |
|
|
| - `system`: optional English personality request. An empty string selects the original |
| ChillText personality: lowercase, extremely casual, no emojis or em dashes, and restrained, |
| context-appropriate current slang. |
| - `input`: the user's real message or question to the assistant. |
| - `agentOutput`: the assistant's normal answer before style transfer. |
| - `output`: the same answer rewritten in ChillText style. Separate chat bubbles are joined by |
| a blank line (`\n\n`). |
| - `n_msgs`: number of output bubbles, always 1–4. |
| - `batch_id`: generation bookkeeping. |
|
|
| The optional `system` prompt changes personality rather than factual content. Examples include |
| warm, dry, snarky, concise, patient, deadpan, playful, or direct styles. A deliberately small |
| subset explicitly permits ordinary profanity. Those prompts teach occasional, context-aware |
| swearing while prohibiting slurs, hate, threats, and abusive targeting. Profanity is rejected in |
| all empty-system and ordinary-system rows. |
|
|
| ## Release statistics |
|
|
| | measure | value | |
| |---|---:| |
| | rows | 200,000 | |
| | default/empty-system rows | 121,551 | |
| | custom-system rows | 78,449 | |
| | profanity-permitted system rows | 4,061 | |
| | rows containing exact-copy invariants | 80,216 | |
| | 1 / 2 / 3 / 4 message rows | 68,635 / 98,734 / 26,566 / 6,065 | |
|
|
| ## Quality controls |
|
|
| Rows were generated with GPT-5.6 Luna at low reasoning. Reasoning was ignored at the transport |
| layer and is not included in the dataset. Every retained row passed deterministic checks for: |
|
|
| - exact preservation of URLs, emails, paths, commands, model names, versions, dates, times, |
| prices, percentages, measurements, ticket/order IDs, and other numeric identifiers; |
| - coherent 1–4-message output formatting; |
| - no emoji, em dash, en dash, or dated/forced internet slang; |
| - lowercase default output except case-sensitive exact-copy spans; |
| - no duplicate interactions and no unchanged `agentOutput`/`output` pairs; |
| - profanity only when the explicit system prompt permits it. |
|
|
| Release candidates also received a Luna major-defect review for incoherence, contradictions, |
| invented or unrelated details, changed uncertainty or refusal behavior, and safety-critical |
| omissions. Introduced-anchor candidates received a separate relevance review. Rows rejected by |
| either review were regenerated, and every replacement tail was reviewed again before release. |
|
|
| Automated validators cannot prove perfect semantic equivalence. Applications should keep their |
| normal safety checks and evaluate the model on their own domain, especially for medical, legal, |
| financial, or other high-stakes text. |
|
|
| ## Suggested training prompt |
|
|
| Use `system` as the model's system message when it is nonempty, omit the system turn otherwise, |
| and send this user message: |
|
|
| ```text |
| rewrite the agent output in chilltext style using the user's message as context. |
| |
| user: |
| {input} |
| |
| agent output: |
| {agentOutput} |
| |
| return only the rewritten chat message or messages, separated by a blank line. use 1 to 4 messages total and never more than 4. |
| ``` |
|
|
| Train only on `output` as the assistant completion. Gemma 4 natively supports system messages, |
| so personality prompts can be supplied directly in the `system` role. |
|
|
| ## Generation and intended use |
|
|
| The data is intended for supervised style-transfer training and evaluation. Facts are synthetic; |
| do not treat examples as real news, medical records, transactions, or operational instructions. |
| The `.example.com`/`.example` resources and 555 phone numbers are deliberately non-production. |
|
|