ShiningValiant-GGUF / README.md
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metadata
base_model: ValiantLabs/ShiningValiant
language:
  - en
library_name: transformers
license: llama2
model_type: llama
quantized_by: mradermacher
tags:
  - shining-valiant
  - valiant
  - valiant-labs
  - llama
  - llama-2
  - llama-2-chat
  - 70b

About

static quants of https://huggingface.co/ValiantLabs/ShiningValiant

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 26.4
GGUF IQ3_XS 29.2
GGUF IQ3_S 30.9 beats Q3_K*
GGUF Q3_K_S 30.9
GGUF IQ3_M 31.9
GGUF Q3_K_M 34.2 lower quality
GGUF Q3_K_L 37.1
GGUF IQ4_XS 38.1
GGUF Q4_K_S 40.2 fast, recommended
GGUF Q4_K_M 42.4 fast, recommended
GGUF Q5_K_S 48.4
PART 1 PART 2 Q5_K_M 49.7
PART 1 PART 2 Q6_K 57.5 very good quality
PART 1 PART 2 Q8_0 74.2 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.