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    hf-zero-shot

    by Kevin Cline

    Classify any text or file into custom categories using Hugging Face's BART-MNLI model with no training required.

    Updated May 2026
    77 views
    Security scanned

    $12

    One-time purchase

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Categorize incoming support tickets into routing departments automatically.
    • Perform sentiment or topic analysis on bulk exported text data.
    • terminal, network, env_vars automation included
    • Includes example output and usage patterns
    • Instant install

    Sample Output

    A real example of what this skill produces.

    TEXT: The quarterly earnings beat expectations TOP: finance (98.2%) finance 98.2% ################### politics 1.1% sports 0.4% entertainment 0.3%

    Results saved to: ~/.hf-zero-shot/zero_shot_20231027_120000.json

    About This Skill

    Automated Text Classification via BART-MNLI

    This skill provides a robust, zero-shot text classification engine for AI agents. By leveraging the Facebook BART-Large-MNLI model via Hugging Face's Inference API, it solves the problem of categorizing unstructured data without the need for custom training data or fine-tuning. It allows developers to define dynamic taxonomies on the fly and receive confidence-scored results instantly.

    What it does

    At a high level, the skill takes input text or files and maps them against a customizable list of labels. It handles API communication, model loading states, and result persistence. Unlike raw prompting, which can be inconsistent or hallucinate labels, this skill uses a specialized NLI (Natural Language Inference) model specifically architected for cross-label entailment.

    Why use this skill

    • Consistency: Returns structured, mathematical confidence scores for every label provided.
    • Scale: Processes individual strings or batch processes entire text files via a simple flag.
    • Persistence: Automatically logs every classification run to a local JSON database (~/.hf-zero-shot/) for audit trails or further analysis.
    • Efficiency: Uses specialized inference endpoints rather than general LLM tokens for classification tasks.

    Supported Tools

    • Hugging Face Inference API (BART-Large-MNLI)
    • Python-based execution for local data security
    • JSON-based structured output

    Use Cases

    • Categorize incoming support tickets into routing departments automatically.
    • Perform sentiment or topic analysis on bulk exported text data.
    • Sort news feeds or social media mentions into custom defined interest areas.
    • Tag internal document repositories with dynamic, non-predefined taxonomies.

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    Security Scanned

    Passed automated security review

    Permissions

    Terminal / Shell
    Network Access
    Environment Variables

    Allowed Hosts

    huggingface.co
    api-inference.huggingface.co

    Tags

    nlp
    text-classification
    hugging-face
    machine-learning
    data-processing
    zero-shot

    Creator

    K
    Kevin Cline

    ClawdWorks

    Builder of autonomous AI agents and Claude Code skills. ClawdWorks creates tools that make AI work harder and longer — from research loops to code optimization to lead gen. Powered by Claude Opus 4.6 + Codex 5.4.

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