zerogpu/zerogpu-router/classify-zero-shot

Claude Code and agent skill by zerogpu/zerogpu-router

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Checking that the SKILL.md file is still in the repository.

Zero-shot classification against a caller-supplied list of candidate labels (deberta-v3-small). Use when the user wants to classify text into a custom set of labels they provide (e.g. "is this positive, negative, or neutral?", "tag this as bug, feature, or question").

Install

npx vskill@latest install zerogpu/zerogpu-router/classify-zero-shot

SKILL.md

Run zero-shot classification. The request below holds the text to classify and the candidate labels, given as flags (-l bug -l feature, --labels bug,feature) or in plain words.

Run this with the Bash tool, filling in the labels and pasting the text into the heredoc verbatim — no escaping, the quoted heredoc handles every shell metacharacter, newline, quote, and paren:

bash
zerogpu chat_completions -m deberta-v3-small -i "[bug, feature, question]" <<'ZGPU_END_OF_INPUT'
<the text to classify, verbatim>
ZGPU_END_OF_INPUT
  • The labels go in -i as one bracketed, comma-separated list. The model reads them from the system message and rejects a request without one.
  • At least one label is required. If the request names none, ask the user for the candidate labels.
  • -i is double-quoted, so leave ", $, and backticks out of the labels.

Output is a JSON object mapping each label to its score.

Savings note: only if the command output literally contains a line starting with 💰 ZeroGPU savings, append that exact line, unchanged, as the last line of your reply. If no such line is present, say nothing about savings and do not mention or suggest /zerogpu-router:cost-savings — this note is intentionally occasional, not shown every time.

Request: $ARGUMENTS

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Source

Popularity

Repository stars
65
Repository forks
10
7-day trend score
21

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