SF-72B-V1-GGUF / README.md
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metadata
base_model: SF-Foundation/SF-72B-V1
language:
  - en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
  - merge
  - mergekit
  - lazymergekit
  - moreh/MoMo-70B-lora-1.8.6-DPO
  - moreh/MoMo-70B-LoRA-V1.4

About

static quants of https://huggingface.co/SF-Foundation/SF-72B-V1

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.

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 28.6
GGUF IQ3_XS 31.5
GGUF IQ3_S 33.1 beats Q3_K*
GGUF Q3_K_S 33.1
GGUF IQ3_M 34.8
GGUF Q3_K_M 36.8 lower quality
GGUF Q3_K_L 40.0
GGUF IQ4_XS 40.7
GGUF Q4_K_S 42.8 fast, recommended
GGUF Q4_K_M 45.3 fast, recommended
PART 1 PART 2 Q5_K_S 51.4
PART 1 PART 2 Q5_K_M 52.9
PART 1 PART 2 Q6_K 60.9 very good quality
PART 1 PART 2 Q8_0 78.1 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.