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KwaiCoder-DS-V2-Lite-Base-non-MLA-GGUF

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Duplicate from mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF

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Co-authored-by: team mradermacher <[email protected]>

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+ ---
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+ base_model: Kwaipilot/KwaiCoder-DS-V2-Lite-Base
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+ language:
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+ - multilingual
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+ library_name: transformers
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+ license: mit
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+ quantized_by: mradermacher
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+ tags:
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+ - code-generation
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+ - transformers
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+ ---
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+ ## About
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+
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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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+ static quants of https://huggingface.co/Kwaipilot/KwaiCoder-DS-V2-Lite-Base
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+
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+ <!-- provided-files -->
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+ weighted/imatrix quants are available at https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-i1-GGUF
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+ ## Usage
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+
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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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+
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+ ## Provided Quants
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+
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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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+
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+ | Link | Type | Size/GB | Notes |
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+ |:-----|:-----|--------:|:------|
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q2_K.gguf) | Q2_K | 6.5 | |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q3_K_S.gguf) | Q3_K_S | 7.6 | |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q3_K_M.gguf) | Q3_K_M | 8.2 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q3_K_L.gguf) | Q3_K_L | 8.6 | |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.IQ4_XS.gguf) | IQ4_XS | 8.7 | |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q4_K_S.gguf) | Q4_K_S | 9.6 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q4_K_M.gguf) | Q4_K_M | 10.5 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q5_K_S.gguf) | Q5_K_S | 11.2 | |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q5_K_M.gguf) | Q5_K_M | 12.0 | |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q6_K.gguf) | Q6_K | 14.2 | very good quality |
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+ | [GGUF](https://huggingface.co/mradermacher/KwaiCoder-DS-V2-Lite-Base-GGUF/resolve/main/KwaiCoder-DS-V2-Lite-Base.Q8_0.gguf) | Q8_0 | 16.8 | fast, best quality |
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+
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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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+
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+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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+
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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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+
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+ ## FAQ / Model Request
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+
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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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+
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+ ## Thanks
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+
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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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+
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+ <!-- end -->