mradermacher/L3-Super-Nova-RP-8B-GGUF

About

quantize_version: 2 -->

output_tensor_quantised: 1 -->

convert_type: hf -->

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static quants of https://huggingface.co/Casual-Autopsy/L3-Super-Nova-RP-8B

provided-files --> weighted/imatrix quants are available at https://huggingface.co/mradermacher/L3-Super-Nova-RP-8B-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

| Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | GGUF | Q2_K | 3.3 | | | GGUF | IQ3_XS | 3.6 | | | GGUF | Q3_K_S | 3.8 | | | GGUF | IQ3_S | 3.8 | beats Q3_K* | | GGUF | IQ3_M | 3.9 | | | GGUF | Q3_K_M | 4.1 | lower quality | | GGUF | Q3_K_L | 4.4 | | | GGUF | IQ4_XS | 4.6 | | | GGUF | Q4_K_S | 4.8 | fast, recommended | | GGUF | Q4_K_M | 5.0 | fast, recommended | | GGUF | Q5_K_S | 5.7 | | | GGUF | Q5_K_M | 5.8 | | | GGUF | Q6_K | 6.7 | very good quality | | GGUF | Q8_0 | 8.6 | fast, best quality | | GGUF | f16 | 16.2 | 16 bpw, overkill |

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):



And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.

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