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metadata
base_model: jondurbin/airoboros-34b-3.3
datasets:
  - jondurbin/airoboros-3.2
  - bluemoon-fandom-1-1-rp-cleaned
  - boolq
  - jondurbin/gutenberg-dpo-v0.1
  - LDJnr/Capybara
  - jondurbin/cinematika-v0.1
  - glaiveai/glaive-function-calling-v2
  - grimulkan/LimaRP-augmented
  - piqa
  - Vezora/Tested-22k-Python-Alpaca
  - mattpscott/airoboros-summarization
  - unalignment/toxic-dpo-v0.2
language:
  - en
library_name: transformers
license: other
license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE
license_name: yi-license
quantized_by: mradermacher

About

static quants of https://huggingface.co/jondurbin/airoboros-34b-3.3

weighted/imatrix quants are available at https://huggingface.co/mradermacher/airoboros-34b-3.3-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 13.5
GGUF IQ3_XS 14.9
GGUF Q3_K_S 15.6
GGUF IQ3_S 15.7 beats Q3_K*
GGUF IQ3_M 16.2
GGUF Q3_K_M 17.3 lower quality
GGUF Q3_K_L 18.8
GGUF IQ4_XS 19.3
GGUF Q4_K_S 20.2 fast, recommended
GGUF Q4_K_M 21.3 fast, recommended
GGUF Q5_K_S 24.3
GGUF Q5_K_M 25.0
GGUF Q6_K 28.9 very good quality
GGUF Q8_0 37.1 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.