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mradermacher
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Viking-SlimSonnet-v0.2-7B-GGUF

Transformers
GGUF
text-generation-inference
unsloth
llama
trl
sft
Inference Endpoints
conversational
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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/mpasila/Viking-SlimSonnet-v0.2-7B
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model: mpasila/Viking-SlimSonnet-v0.2-7B
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+ datasets:
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+ - Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
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+ - mpasila/Sonnet3.5-SlimOrcaDedupCleaned-4k-context
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+ language:
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+ - en
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+ - fi
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+ - sv
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+ - no
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+ - da
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+ - is
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+ - nn
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+ library_name: transformers
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+ license: apache-2.0
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+ quantized_by: mradermacher
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+ tags:
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+ - text-generation-inference
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+ - transformers
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+ - unsloth
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+ - llama
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+ - trl
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+ - sft
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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/mpasila/Viking-SlimSonnet-v0.2-7B
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+
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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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+
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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/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q2_K.gguf) | Q2_K | 3.1 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.IQ3_XS.gguf) | IQ3_XS | 3.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.IQ3_S.gguf) | IQ3_S | 3.6 | beats Q3_K* |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q3_K_S.gguf) | Q3_K_S | 3.6 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.IQ3_M.gguf) | IQ3_M | 3.7 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q3_K_L.gguf) | Q3_K_L | 4.2 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.IQ4_XS.gguf) | IQ4_XS | 4.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q4_K_S.gguf) | Q4_K_S | 4.5 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q4_K_M.gguf) | Q4_K_M | 4.7 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q5_K_S.gguf) | Q5_K_S | 5.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q5_K_M.gguf) | Q5_K_M | 5.5 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q6_K.gguf) | Q6_K | 6.3 | very good quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.Q8_0.gguf) | Q8_0 | 8.1 | fast, best quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Viking-SlimSonnet-v0.2-7B-GGUF/resolve/main/Viking-SlimSonnet-v0.2-7B.f16.gguf) | f16 | 15.2 | 16 bpw, overkill |
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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 -->