# [Feedback Wanted] Low-Latency LLM Guardrails Using a 14M Parameter Discriminator

> Source: <https://discuss.huggingface.co/t/feedback-wanted-low-latency-llm-guardrails-using-a-14m-parameter-discriminator/177768#post_1>
> Published: 2026-07-13 09:03:31+00:00

Hi everyone,

I have released ** DeshwalX/electra-small-prompt-injection-v1**, a multi-label classifier for low-latency LLM guardrails.

Many prompt injection detectors rely on large autoregressive models that introduce processing latency. This project tests the baseline efficiency of a compact encoder backbone by fine-tuning ** google/electra-small-discriminator** (~14M parameters) to detect four independent safety vectors in a single forward pass.

**WildGuard Test Benchmark Evaluation:**

**Micro F1:** 90.00% | **Macro F1:** 89.00%

**Prompt Adversarial (Jailbreaks):** 1.00 F1

**Response Refusal:** 0.86 F1

**Prompt Harmful:** 0.88 F1

**Response Harmful:** 0.81 F1

**Model Repository:** [DeshwalX/electra-small-prompt-injection-v1 · Hugging Face](https://huggingface.co/DeshwalX/electra-small-prompt-injection-v1)

I am looking for community feedback to improve **Version 1**. Please test the model on your own data and share:

Edge cases where the model fails or misses an injection.

Examples of false positives on benign inputs.

Suggestions for architecture configurations or loss weight balancing for the next iteration.