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tiny-classifiers

Train a 17M-parameter text classifier in a minute, with labels from a big AI model, and know when it beats an API. Recipe, tutorial, results on 10 tasks, phone trainer.

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GITHUB · launched Sep 27, 2026 · 70 upvotes (top 12%) · 0 views

Niche: machine learning developer tools · 303 launches, 11 in the last 7 days ▼ -45% · Explore this niche →

Category and tags

  • Horizontal
  • Model & infra
  • Developer
  • AI-native
  • Hobby / open-source project

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Could you build this?

Partial While an interface and basic PyTorch script can be scaffolded, efficient distillation of LLM labels into lightweight classifiers and on-device deployment requires ML engineering know-how.

What it would actually take: Requires a pipeline combining LLM synthetic labeling (OpenAI/Anthropic API), tokenization, and fine-tuning lightweight encoder models (e.g., MobileBERT, ModernBERT, or small Transformers) using PyTorch or ONNX Runtime. Mobile/phone export requires quantization (INT8) and CoreML/TFLite model conversion pipelines.

Competitors

Other products that read as similar to this one : 223 launches clear the similarity bar, closest 8 shown.

Attention rank: #39 of 224 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 326 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.