This is the Linux app named Synthetic Data Kit whose latest release can be downloaded as synthetic-data-kitsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Synthetic Data Kit with OnWorks for free.
Befolgen Sie diese Anweisungen, um diese App auszuführen:
- 1. Diese Anwendung auf Ihren PC heruntergeladen.
- 2. Geben Sie in unserem Dateimanager https://www.onworks.net/myfiles.php?username=XXXXX den gewünschten Benutzernamen ein.
- 3. Laden Sie diese Anwendung in einem solchen Dateimanager hoch.
- 4. Starten Sie den OnWorks Linux-Online- oder Windows-Online-Emulator oder den MACOS-Online-Emulator von dieser Website.
- 5. Rufen Sie vom gerade gestarteten OnWorks Linux-Betriebssystem aus unseren Dateimanager https://www.onworks.net/myfiles.php?username=XXXXX mit dem gewünschten Benutzernamen auf.
- 6. Laden Sie die Anwendung herunter, installieren Sie sie und führen Sie sie aus.
SCREENSHOTS
Ad
Synthetisches Datenkit
BESCHREIBUNG
Synthetic Data Kit is a CLI-centric toolkit for generating high-quality synthetic datasets to fine-tune Llama models, with an emphasis on producing reasoning traces and QA pairs that line up with modern instruction-tuning formats. It ships an opinionated, modular workflow that covers ingesting heterogeneous sources (documents, transcripts), prompting models to create labeled examples, and exporting to fine-tuning schemas with minimal glue code. The kit’s design goal is to shorten the “data prep” bottleneck by turning dataset creation into a repeatable pipeline rather than ad-hoc notebooks. It supports generation of rationales/chain-of-thought variants, configurable sampling, and guardrails so outputs meet format constraints and quality checks. Examples and guides show how to target task-specific behaviors like tool use or step-by-step reasoning, then save directly into training-ready files.
Eigenschaften
- Four-stage CLI pipeline from ingest to export
- Generation of QA pairs and reasoning traces
- Configurable prompting, sampling, and filters
- Training-ready output formats for fine-tuning
- Quality checks and schema validation
- Examples targeting task-specific reasoning
Programmiersprache
Python
Kategorien
This is an application that can also be fetched from https://sourceforge.net/projects/synthetic-data-kit.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
