---
license: apache-2.0
library_name: transformers.js
pipeline_tag: token-classification
base_model: google/electra-small-discriminator
base_model_relation: finetune
language:
  - en
tags:
  - eye-grep
  - log-analysis
  - onnx
---

# eye-grep tagger — electra-small (distilled)

The small, browser-friendly tagger for **eye-grep**, a log colorizer that highlights
ids, timestamps, IPs and repeated strings in server logs. It is a **token classifier**
that labels each content token of a log line with one of 11 tags.

A **google/electra-small-discriminator** student (WordPiece), **knowledge-distilled**
from the [opsbr/eye-grep-deberta-v3-small](https://huggingface.co/opsbr/eye-grep-deberta-v3-small)
teacher (the two have different tokenizers, so distillation is done on aligned
per-content-token logits). At ~14 MB int8 it is ideal for an in-browser WebGPU/WASM
build — the eye-grep web demo and `eye-grep/react` use it by default. For maximum
accuracy (CLI / server) use the deberta teacher.

## Tag schema (11 classes)

`PUNCT  WORD  NUM  RAND  IP  DURATION  SIZE  TIMESTAMP  LEVEL  URL  PATH`

`RAND` is a high-entropy id (uuid / hash / token); `NUM`, `SIZE`, `DURATION` are
numeric values; `TIMESTAMP`, `IP`, `URL`, `PATH`, `LEVEL` are self-explanatory;
`WORD`/`PUNCT` are ordinary text.

## Files

ONNX in the transformers.js layout — `onnx/model.onnx` (fp32, for WebGPU) and
`onnx/model_quantized.onnx` (int8, for WASM) — plus the WordPiece tokenizer.

## Usage

eye-grep React component:

```tsx
import { LogView } from 'eye-grep/react';
<LogView text={logs} model="opsbr/eye-grep-electra-small" device="webgpu" />
```

transformers.js (browser):

```js
import { AutoTokenizer, AutoModelForTokenClassification } from '@huggingface/transformers';
const tokenizer = await AutoTokenizer.from_pretrained('opsbr/eye-grep-electra-small');
const model = await AutoModelForTokenClassification.from_pretrained(
  'opsbr/eye-grep-electra-small', { dtype: 'q8', device: 'webgpu' });
```

## Training data

Distilled from the deberta teacher on the synthetic, fully-owned
[opsbr/eye-grep](https://huggingface.co/datasets/opsbr/eye-grep) gold set
(Apache-2.0) — no third-party log data.

## Notes

- A distilled student: smaller and faster than the deberta teacher at some accuracy cost.
- Same 11-tag schema and tokenizer-alignment contract as the teacher.