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Model: mradermacher/prompt-injection-judge-8b-GGUF Source: Original Platform
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---
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base_model: hlyn/prompt-injection-judge-8b
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language:
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- en
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library_name: transformers
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license: llama3.1
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mradermacher:
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readme_rev: 1
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quantized_by: mradermacher
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tags:
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- security
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- prompt-injection
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- cyber-security
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- orpo
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- gguf
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- llama-cpp
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- reasoning
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---
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## About
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### vocab_type: -->
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<!-- ### tags: -->
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<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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static quants of https://huggingface.co/hlyn/prompt-injection-judge-8b
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<!-- provided-files -->
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#prompt-injection-judge-8b-GGUF).***
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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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## Usage
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If you are unsure how to use GGUF files, refer to one of [TheBloke's
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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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more details, including on how to concatenate multi-part files.
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## Provided Quants
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q2_K.gguf) | Q2_K | 3.3 | |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q3_K_S.gguf) | Q3_K_S | 3.8 | |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q3_K_L.gguf) | Q3_K_L | 4.4 | |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.IQ4_XS.gguf) | IQ4_XS | 4.6 | |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q5_K_S.gguf) | Q5_K_S | 5.7 | |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q5_K_M.gguf) | Q5_K_M | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q6_K.gguf) | Q6_K | 6.7 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/prompt-injection-judge-8b-GGUF/resolve/main/prompt-injection-judge-8b.f16.gguf) | f16 | 16.2 | 16 bpw, overkill |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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And here are Artefact2's thoughts on the matter:
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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## FAQ / Model Request
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See https://huggingface.co/mradermacher/model_requests for some answers to
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questions you might have and/or if you want some other model quantized.
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## Thanks
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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me use its servers and providing upgrades to my workstation to enable
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this work in my free time.
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<!-- end -->
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version https://git-lfs.github.com/spec/v1
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oid sha256:42b68c218144429a5f9e026d597121bde468e91631f7b7adde608c34c55991df
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size 4484363584
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oid sha256:9060b8a3fd5550d46e1ad09d10b8e912baf8a202e35da3d8aa2b63853f77fd1e
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size 3179132224
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oid sha256:07116a6fea12ae5e4a888609222fa2c63c3b9ab352bdff758cc05f259a141409
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size 4321957184
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size 4018918720
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oid sha256:ce85ab54c4d8b9e05b1da7aaf1f36ebef48a75fad7970485365e034a1370174b
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size 3664500032
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oid sha256:04d6958840963a074bd5af3208adab673fc95f476ba206c1e7fe358954f293e4
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size 4920735040
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size 5732988224
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oid sha256:89d5151a649802bd6bb74caf86d55795776fe0efc859bebd0c1c5edfc1a78fc8
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size 5599294784
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size 6596007232
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size 16068891968
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