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-`huggingface` -- a generic detector class that is intended to be compatible with any [AutoModelForSequenceClassification](https://huggingface.co/docs/transformers/en/model_doc/auto#transformers.AutoModelForSequenceClassification) or a specific kind of [AutoModelForCausalLM](https://huggingface.co/docs/transformers/en/model_doc/auto#transformers.AutoModelForCausalLM), namely [GraniteForCausalLM](https://github.com/ibm-granite/granite-guardian); this detector exposes `/api/v1/text/contents` and thus, could be configured to be a detector of type: `text_contents` within the FMS Guardrails Orchestrator framework. This detector is also intended to be deployed as a [KServe](https://github.com/kserve/kserve) inference service.
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-`llm_judge` -- Integrates the [vLLM Judge](https://github.com/trustyai-explainability/vllm_judge) library to use LLM-as-a-judge based guardrailing architecture
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-`built_in` -- Small, lightweight detection functions that are deployed out-of-the-box alongside the [Guardrails Orchestrator]([https://github.com/foundation-model-stack/fms-guardrails-orchestrator). The built-in detectors provide a number of heuristic or algorithmic detection functions, such as:
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-`builtIn` -- Small, lightweight detection functions that are deployed out-of-the-box alongside the [Guardrails Orchestrator](https://github.com/foundation-model-stack/fms-guardrails-orchestrator). The built-in detectors provide a number of heuristic or algorithmic detection functions, such as:
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- Regex-based detections, with pre-written regexes for flagging various Personally Identifiable Information items like emails or phone numbers, as well as the ability to provide custom regexes
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- File-type validations, for verifying if model input/output is valid JSON, XML, or YAML
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