THE CURIOUS SIDE OF AI
TEXT / DATASET GUIDE
smol-smoltalk
A conversation mixture designed for small-model instruction tuning. Select a small, relevant subset; the full dataset is not tiny.
Source reviewed 2026-10-24 · AiBrainWorX editorial guide
- Purpose
- Text instruction tuning
- Format
- messages: role/content; source
- Workflow
- tiny-text-lora
- License
- apache-2.0
01 / COMPATIBILITY
Recipe-compatible after subset preparation
Verify exact data rights, prepare a small local subset and evaluate on held-out data. No remote dataset code is executed.
02 / PREPARE LOCALLY
Keep the first run small
- Review the selected source subset, license and data rights.
- Prepare the format required by the chosen trainer. Audio, image classification and text SFT are different workflows.
- Set aside evaluation examples and inspect the final records before training.
- For the launcher text worker, choose a local JSONL file and supported HF checkpoint, then run Preflight.
Our test status
Metadata/schema reviewed, not downloaded or used in training.
03 / ORIGINAL SOURCE
Review files and terms
This is an original concise guide, not a mirror or relicense of the dataset.
Open original publisher ↗Reviewed source revision: f73fe857d519ff6ac5af2ea67c4d3834da7b8bcc