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| tags: |
| - encoderfile |
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| # Encoderfile Models |
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| **IMPORTANT NOTE: This repository is now deprecated!** Please check out our new [`encoderfiles` collection](https://huggingface.co/collections/mozilla-ai/encoderfiles) to find your favorite prebuilt encoderfiles. |
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| Pre-built [encoderfiles](https://github.com/mozilla-ai/encoderfile) for popular Hugging Face embedding models — self-contained executables that run as embedding servers with no Python or ML dependencies required. |
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| ## Available Models |
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| | Model | Details | |
| |---|---| |
| | [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2/) | 384-dim, English sentence embeddings | |
| | [deepset/deberta-v3-base-injection](https://huggingface.co/deepset/deberta-v3-base-injection) | DeBERTa-variant prompt injection classification model | |
| | [JasperLS/deberta-v3-base-injection](https://huggingface.co/JasperLS/deberta-v3-base-injection) | DeBERTa-variant prompt injection classification model | |
| | [JasperLS/gelectra-base-injection](https://huggingface.co/JasperLS/gelectra-base-injection) | gELECTRA-variant prompt injection classification model | |
| | [protectai/deberta-v3-base-prompt-injection-v2](https://huggingface.co/protectai/deberta-v3-base-prompt-injection-v2) | DeBERTa-variant prompt injection classification model | |
| | [protectai/deberta-v3-small-prompt-injection-v2](https://huggingface.co/protectai/deberta-v3-small-prompt-injection-v2) | DeBERTa-variant prompt injection classification model | |
| | [protectai/deberta-v3-base-prompt-injection](https://huggingface.co/protectai/deberta-v3-base-prompt-injection) | DeBERTa-variant prompt injection classification model | |
| | [protectai/distilroberta-base-rejection-v1](https://huggingface.co/protectai/distilroberta-base-rejection-v1) | DistilRoBERTa-variant prompt injection classification model | |
| | [DuoGuard/DuoGuard-0.5B](https://huggingface.co/DuoGuard/DuoGuard-0.5B) | Content moderation model based on Qwen2.5-0.5B | |
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| More models coming soon. |
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| ## Usage |
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| Each model directory contains platform-specific binaries. Download the one for your platform, make it executable, and run: |
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| ```bash |
| # Serve embeddings over HTTP |
| ./all-MiniLM-L6-v2.aarch64-apple-darwin.encoderfile serve |
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| # Or infer directly from the CLI |
| ./all-MiniLM-L6-v2.aarch64-apple-darwin.encoderfile infer "this is a test" |
| ``` |
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| If you don't see the model you want or are using an exotic architecture, check out our guide on [Building encoderfiles](https://mozilla-ai.github.io/encoderfile/reference/building/). |
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| ## About |
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| These encoderfiles are built and published by [mozilla-ai](https://huggingface.co/mozilla-ai) using the [Encoderfile](https://github.com/mozilla-ai/encoderfile) tool. To build your own, see the [Encoderfile documentation](https://mozilla-ai.github.io/encoderfile). |
