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metadata
base_model: sophosympatheia/Midnight-Rose-103B-v2.0.3
language:
  - en
library_name: transformers
license: llama2
quantized_by: mradermacher

About

static quantize of https://huggingface.co/sophosympatheia/Midnight-Rose-103B-v2.0.3/

weighted/imatrix wuants can be found at https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-i1-GGUF

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs 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 38.3
GGUF IQ3_XS 42.3
GGUF Q3_K_XS 42.4
GGUF IQ3_S 44.7 beats Q3_K*
GGUF Q3_K_S 44.9
GGUF IQ3_M 46.2
PART 1 PART 2 Q3_K_M 50.0 lower quality
PART 1 PART 2 Q3_K_L 54.5
PART 1 PART 2 IQ4_XS 55.7
PART 1 PART 2 Q4_K_S 59.0 fast, recommended
PART 1 PART 2 Q4_K_M 62.3 fast, recommended
PART 1 PART 2 Q5_K_S 71.4
PART 1 PART 2 Q5_K_M 73.3
PART 1 PART 2 Q6_K 85.1 very good quality
PART 1 PART 2 PART 3 Q8_0 110.0 fast, best quality

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

image.png

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.