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Model: mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF Source: Original Platform
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llama-3.1-Asian-Bllossom-8B-Translator.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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---
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base_model: MLP-KTLim/llama-3.1-Asian-Bllossom-8B-Translator
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language:
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- ko
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- vi
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- id
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- km
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- th
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library_name: transformers
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license: llama3.1
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quantized_by: mradermacher
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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: nicoboss -->
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static quants of https://huggingface.co/MLP-KTLim/llama-3.1-Asian-Bllossom-8B-Translator
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<!-- provided-files -->
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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/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q2_K.gguf) | Q2_K | 3.3 | |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q3_K_S.gguf) | Q3_K_S | 3.8 | |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q3_K_L.gguf) | Q3_K_L | 4.4 | |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.IQ4_XS.gguf) | IQ4_XS | 4.6 | |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.8 | fast on arm, low quality |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q5_K_S.gguf) | Q5_K_S | 5.7 | |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q5_K_M.gguf) | Q5_K_M | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q6_K.gguf) | Q6_K | 6.7 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/llama-3.1-Asian-Bllossom-8B-Translator-GGUF/resolve/main/llama-3.1-Asian-Bllossom-8B-Translator.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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
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<!-- end -->
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llama-3.1-Asian-Bllossom-8B-Translator.IQ4_XS.gguf
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version https://git-lfs.github.com/spec/v1
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size 4484368224
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llama-3.1-Asian-Bllossom-8B-Translator.Q2_K.gguf
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llama-3.1-Asian-Bllossom-8B-Translator.Q3_K_L.gguf
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size 4321961824
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llama-3.1-Asian-Bllossom-8B-Translator.Q4_0_4_4.gguf
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size 4920739680
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size 4692674400
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llama-3.1-Asian-Bllossom-8B-Translator.Q5_K_M.gguf
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size 5732992864
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oid sha256:5f00ac3d5c67c035a0141aec94dcdc5b68daa267a2325230d21cb8dc8cd1d620
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size 6596011872
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oid sha256:118c3d5b169d249dcd5037126dd69ca8f4da0dbd9c6fb958862d87a1244a4108
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size 8540776288
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oid sha256:7771aaac27f2cdc8299e497ab682a1d69f778c206155eb1ab3e0790d7daa49f6
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size 16068896608
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