@cjzafir: Before Claude Fable 5 got banned, I turned all my fine-tuning research and experiments into a product: http://Finetuner…

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Summary

Developer @cjzafir announces Finetuner.dev, a CLI tool that uses orchestrator models like Codex 5.5 and Chinese models to generate high-quality, handcrafted datasets for fine-tuning small language models (1B-30B), claiming 10x lower costs and 5x better quality.

Before Claude Fable 5 got banned, I turned all my fine-tuning research and experiments into a product: http://Finetuner.dev (A CLI for data generation to fine-tune AI models). Finetuner uses Codex 5.5 or Opus 4.8 as the orchestrator and Chinese models (DeepSeek v4 Pro, Kimi K2.7, MiMo v2.5, etc.) to generate dataset rows. This system is unique because these are not Python-script-paraphrased datasets. Each and every row is handcrafted by Chinese models based on the orchestrator model's instructions. Now anyone can generate datasets to fine-tune small language models (1B to 30B models). I achieved 10x lower costs and 5x better dataset quality. Releasing the product in a few days. (I'll open-source the skills.)
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Cached at: 06/16/26, 01:13 AM

Before Claude Fable 5 got banned,

I turned all my fine-tuning research and experiments into a product: http://Finetuner.dev (A CLI for data generation to fine-tune AI models).

Finetuner uses Codex 5.5 or Opus 4.8 as the orchestrator and Chinese models (DeepSeek v4 Pro, Kimi K2.7, MiMo v2.5, etc.) to generate dataset rows.

This system is unique because these are not Python-script-paraphrased datasets. Each and every row is handcrafted by Chinese models based on the orchestrator model’s instructions.

Now anyone can generate datasets to fine-tune small language models (1B to 30B models).

I achieved 10x lower costs and 5x better dataset quality.

Releasing the product in a few days. (I’ll open-source the skills.)

finetuner.dev — turn one idea into a fine-tuning dataset

Source: https://www.finetuner.dev/ CLI for dataset generation tofine-tune models.v1.0.0

No waitlist, Launching in few days.

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