mradermacher/Rotten.Llama-3.2-1B-GGUF

About

quantize_version: 2 -->

output_tensor_quantised: 1 -->

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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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static quants of https://huggingface.co/Novaciano/Rotten.Llama-3.2-1B

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*For a convenient overview and download list, visit our model page for this model.*

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Rotten.Llama-3.2-1B-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 | 0.7 | | | GGUF | Q3_K_S | 0.7 | | | GGUF | Q3_K_M | 0.8 | lower quality | | GGUF | Q3_K_L | 0.8 | | | GGUF | IQ4_XS | 0.8 | | | GGUF | Q4_K_S | 0.9 | fast, recommended | | GGUF | Q4_K_M | 0.9 | fast, recommended | | GGUF | Q5_K_S | 1.0 | | | GGUF | Q5_K_M | 1.0 | | | GGUF | Q6_K | 1.1 | very good quality | | GGUF | Q8_0 | 1.4 | fast, best quality | | GGUF | f16 | 2.6 | 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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