> For the complete documentation index, see [llms.txt](https://docs.mozilla.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mozilla.ai/any-guardrail/api-reference/index/content-safety/bielik-guard.md).

# Bielik Guard

Polish multi-label safety classifier.

Encoder classifier that emits an independent probability (sigmoid) for each of five Polish safety categories: Hate/Aggression, Vulgarities, Sexual Content, Crime, and Self-Harm. It screens a single body of Polish text; category names are read from the model's `id2label` (the published card does not fix an index order), so the entries in `categories` follow the model's own labels.

Verdict mapping onto `GuardrailOutput`:

* `categories` carries every category with its sigmoid probability and a `triggered` flag (probability strictly above `threshold`).
* `valid` is `True` when no category exceeds `threshold`.
* `score` (canonical risk: higher = riskier) is the maximum category probability.

Expected inputs: a single text string, or a `list[str]` for batched classification (the inherited `validate` dispatches list input to `_validate_batch`).

Two variants ship: the 0.1B default is a plain RoBERTa classifier; the 0.5B variant ships custom modeling code and is loaded with `trust_remote_code=True`. The repos are gated (auto-approve) — authenticate with `hf auth login` before first use.

For more information, please see the model cards:

* [Bielik-Guard-0.1B-v1.1](https://huggingface.co/speakleash/Bielik-Guard-0.1B-v1.1) (default).
* [Bielik-Guard-0.5B-v1.1](https://huggingface.co/speakleash/Bielik-Guard-0.5B-v1.1).

## Supported Models

* `speakleash/Bielik-Guard-0.1B-v1.1`
* `speakleash/Bielik-Guard-0.5B-v1.1`

## Constructor

| Parameter   | Type                                                 | Required | Default | Description                                                                                                                                                                                                  |
| ----------- | ---------------------------------------------------- | -------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model_id`  | \`str                                                | None\`   | No      | `None`                                                                                                                                                                                                       |
| `threshold` | `float`                                              | No       | `0.5`   | Per-category probability strictly above which that category is flagged (and the text becomes invalid). Defaults to 0.5.                                                                                      |
| `provider`  | `Optional[Provider[dict[str, Any], dict[str, Any]]]` | No       | `None`  | Optional pre-configured provider. If `None`, a default `HuggingFaceProvider` is built with `multi_label=True` (and `trust_remote_code` enabled only for the 0.5B variant), then the model is loaded eagerly. |

Initialize the Bielik Guard guardrail.

## validate

Default validation pipeline: preprocess -> inference -> postprocess.

**Parameters**

| Parameter    | Type  | Required     | Default | Description |
| ------------ | ----- | ------------ | ------- | ----------- |
| `input_text` | \`str | list\[str]\` | Yes     | —           |

**Returns:** `GuardrailOutput | list[GuardrailOutput]`

## Benchmarks

### Content Safety

| Dataset (rev)                    | Metric | Threshold    | Value    | Harness                 | Source                           | Contam. |
| -------------------------------- | ------ | ------------ | -------- | ----------------------- | -------------------------------- | ------- |
| openai\_moderation (unspecified) | f1     | native-valid | 0.723549 | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| xstest (unspecified)             | fpr    | native-valid | 0.212    | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| wildguardmix (unspecified)       | f1     | native-valid | 0.59434  | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| aegis (unspecified)              | f1     | native-valid | 0.609442 | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| jbb (unspecified)                | f1     | native-valid | 0.469799 | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| orbench (unspecified)            | fpr    | native-valid | 0.154386 | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |

### Toxicity

| Dataset (rev)                | Metric | Threshold    | Value    | Harness                 | Source                           | Contam. |
| ---------------------------- | ------ | ------------ | -------- | ----------------------- | -------------------------------- | ------- |
| real\_toxicity (unspecified) | f1     | native-valid | 0.527919 | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |

## License

* **Vendor:** SpeakLeash / Bielik.AI
* **Default license:** `apache-2.0` (of the default model/service)


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