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tiny-guard-8m-en-prompt-harmfulness-binary-mix

enguard / tiny-guard-8m-en-prompt-harmfulness-binary-mix

Run on huggingface.co
huggingface.co
Total runs: 11
24-hour runs: 0
7-day runs: 2
30-day runs: 10
Model's Last Updated: November 06 2025
text-classification

Introduction of tiny-guard-8m-en-prompt-harmfulness-binary-mix

Model Details of tiny-guard-8m-en-prompt-harmfulness-binary-mix

enguard/tiny-guard-8m-en-prompt-harmfulness-binary-mix

This model is a fine-tuned Model2Vec classifier based on minishlab/potion-base-8m for the prompt-harmfulness-binary found in the nicholasKluge/harmful-text dataset.

Installation 
pip install model2vec[inference]
Usage 
from model2vec.inference import StaticModelPipeline

model = StaticModelPipeline.from_pretrained(
  "enguard/tiny-guard-8m-en-prompt-harmfulness-binary-mix"
)

model.predict(["Example sentence"])
model.predict_proba(["Example sentence"])
Why should you use these models?
  • Optimized for precision to reduce false positives.
  • Extremely fast inference using static embeddings powered by Model2Vec.
This model variant

Below is a quick overview of the model variant and core metrics.

Field Value
Classifies prompt-harmfulness-binary
Base Model minishlab/potion-base-8m
F1 0.9347
Full metrics (JSON) 
{
  "FAIL": {
    "precision": 0.9260112647209422,
    "recall": 0.9385054488842761,
    "f1-score": 0.9322164948453608,
    "support": 3854.0
  },
  "PASS": {
    "precision": 0.942795076031861,
    "recall": 0.931108462455304,
    "f1-score": 0.9369153274166466,
    "support": 4195.0
  },
  "accuracy": 0.9346502671139272,
  "macro avg": {
    "precision": 0.9344031703764015,
    "recall": 0.93480695566979,
    "f1-score": 0.9345659111310037,
    "support": 8049.0
  },
  "weighted avg": {
    "precision": 0.9347586977498035,
    "recall": 0.9346502671139272,
    "f1-score": 0.9346654453530691,
    "support": 8049.0
  }
}
Sample Predictions
Text True Label Predicted Label
answer explain reviewing particular piece kryptonite PASS PASS
also remove old talk page discussions page discretion need speak please post new messages bottom talk page sign four tildes left note talk page likely respond comments either incivil flame bait personal attacks trolling deleted signpost deliveries automatically archived user talk sjones signpost thanks PASS PASS
A new task force to tackle mutilation was being launched, the panel said. PASS FAIL
much quoting barnes lipstadt used source quote barnes words much need sources either put work context historians journalists responding time finally done near end respond points historians written recently many deaths destruction allied bombing human cost expulsion ethnic germans eastern europe drawing conclusions acknowledging abuses repeated according quotes article quotes thing said example add anything thought enough assessment others thought PASS PASS
angle sucks find better one FAIL FAIL
answer explain reviewing particular piece kryptonite PASS PASS
Prediction Speed Benchmarks
Dataset Size Time (seconds) Predictions/Second
1 0.0002 4387.35
1000 0.0396 25266.59
8369 0.3057 27378.94
Other model variants

Below is a general overview of the best-performing models for each dataset variant.

Resources
Citation

If you use this model, please cite Model2Vec: 

@software{minishlab2024model2vec,
  author       = {Stephan Tulkens and {van Dongen}, Thomas},
  title        = {Model2Vec: Fast State-of-the-Art Static Embeddings},
  year         = {2024},
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.17270888},
  url          = {https://github.com/MinishLab/model2vec},
  license      = {MIT}
}

Runs of enguard tiny-guard-8m-en-prompt-harmfulness-binary-mix on huggingface.co

11
Total runs
0
24-hour runs
1
3-day runs
2
7-day runs
10
30-day runs

More Information About tiny-guard-8m-en-prompt-harmfulness-binary-mix huggingface.co Model

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https://choosealicense.com/licenses/mit

tiny-guard-8m-en-prompt-harmfulness-binary-mix huggingface.co

tiny-guard-8m-en-prompt-harmfulness-binary-mix huggingface.co is an AI model on huggingface.co that provides tiny-guard-8m-en-prompt-harmfulness-binary-mix's model effect (), which can be used instantly with this enguard tiny-guard-8m-en-prompt-harmfulness-binary-mix model. huggingface.co supports a free trial of the tiny-guard-8m-en-prompt-harmfulness-binary-mix model, and also provides paid use of the tiny-guard-8m-en-prompt-harmfulness-binary-mix. Support call tiny-guard-8m-en-prompt-harmfulness-binary-mix model through api, including Node.js, Python, http.

tiny-guard-8m-en-prompt-harmfulness-binary-mix huggingface.co Url

https://huggingface.co/enguard/tiny-guard-8m-en-prompt-harmfulness-binary-mix

enguard tiny-guard-8m-en-prompt-harmfulness-binary-mix online free

tiny-guard-8m-en-prompt-harmfulness-binary-mix huggingface.co is an online trial and call api platform, which integrates tiny-guard-8m-en-prompt-harmfulness-binary-mix's modeling effects, including api services, and provides a free online trial of tiny-guard-8m-en-prompt-harmfulness-binary-mix, you can try tiny-guard-8m-en-prompt-harmfulness-binary-mix online for free by clicking the link below.

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https://huggingface.co/enguard/tiny-guard-8m-en-prompt-harmfulness-binary-mix

tiny-guard-8m-en-prompt-harmfulness-binary-mix install

tiny-guard-8m-en-prompt-harmfulness-binary-mix is an open source model from GitHub that offers a free installation service, and any user can find tiny-guard-8m-en-prompt-harmfulness-binary-mix on GitHub to install. At the same time, huggingface.co provides the effect of tiny-guard-8m-en-prompt-harmfulness-binary-mix install, users can directly use tiny-guard-8m-en-prompt-harmfulness-binary-mix installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

tiny-guard-8m-en-prompt-harmfulness-binary-mix install url in huggingface.co:

https://huggingface.co/enguard/tiny-guard-8m-en-prompt-harmfulness-binary-mix

Url of tiny-guard-8m-en-prompt-harmfulness-binary-mix

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Provider of tiny-guard-8m-en-prompt-harmfulness-binary-mix huggingface.co

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