A
AiderClassify millions of rows cheaply offline
vLLM Bulk Text Classifier
Setuproll editorial@setuproll84.0Overall score
A high-throughput batch classifier that runs an open model under vLLM to label huge datasets without per-call API fees. For data teams that need sentiment, topic or moderation labels across millions of rows on their own GPUs.
84.0Score
5Components
Install this build
terminal
pip install vllm && python classify.pyComponents
Model
- Qwen3 8B Instruct
- Gemma 3 12B for harder labels
Stack
- vLLM offline batching
- Polars
- Pydantic output parsing
Hardware
- 1x RTX 4090 24GB
- Scales linearly with more GPUs
How it works
- Load the dataset and build prompt templates per row
- vLLM processes thousands of prompts per batch
- Constrain output to a fixed JSON label schema
- Write labeled results back to parquet
Rules
- Use guided decoding so labels stay in the allowed set
- Checkpoint progress so a crash never reruns everything
Summary
A high-throughput batch classifier that runs an open model under vLLM to label huge datasets without per-call API fees. For data teams that need sentiment, topic or moderation labels across millions of rows on their own GPUs.
84.0 score
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