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metadata
base_model: CausalLM/35b-beta-long
datasets:
  - JosephusCheung/GuanacoDataset
  - meta-math/MetaMathQA
  - jondurbin/airoboros-3.1
  - WizardLM/WizardLM_evol_instruct_V2_196k
  - RyokoAI/ShareGPT52K
  - RyokoAI/Fandom23K
  - milashkaarshif/MoeGirlPedia_wikitext_raw_archive
  - wikipedia
  - wiki_lingua
  - garage-bAInd/Open-Platypus
  - LDJnr/Puffin
  - BAAI/COIG
  - TigerResearch/tigerbot-zhihu-zh-10k
  - liwu/MNBVC
  - teknium/openhermes
  - CausalLM/Refined-Anime-Text
  - microsoft/orca-math-word-problems-200k
  - m-a-p/CodeFeedback-Filtered-Instruction
language:
  - en
  - zh
  - ja
  - de
library_name: transformers
license: wtfpl
quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/CausalLM/35b-beta-long

static quants are available at https://huggingface.co/mradermacher/35b-beta-long-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 i1-IQ1_S 8.6 for the desperate
GGUF i1-IQ1_M 9.2 mostly desperate
GGUF i1-IQ2_XXS 10.3
GGUF i1-IQ2_XS 11.2
GGUF i1-IQ2_S 11.9
GGUF i1-IQ2_M 12.8
GGUF i1-Q2_K 13.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 13.9 lower quality
GGUF i1-IQ3_XS 15.2
GGUF i1-IQ3_S 16.0 beats Q3_K*
GGUF i1-Q3_K_S 16.0 IQ3_XS probably better
GGUF i1-IQ3_M 16.8
GGUF i1-Q3_K_M 17.7 IQ3_S probably better
GGUF i1-Q3_K_L 19.2 IQ3_M probably better
GGUF i1-IQ4_XS 19.3
GGUF i1-Q4_0 20.4 fast, low quality
GGUF i1-Q4_K_S 20.5 optimal size/speed/quality
GGUF i1-Q4_K_M 21.6 fast, recommended
GGUF i1-Q5_K_S 24.4
GGUF i1-Q5_K_M 25.1
GGUF i1-Q6_K 28.8 practically like static Q6_K

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.