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airoboros-70b-3.3-i1-GGUF

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GGUF
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llama-3
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metadata
base_model: jondurbin/airoboros-70b-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/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE
license_name: llama3
quantized_by: mradermacher
tags:
  - llama-3

About

weighted/imatrix quants of https://huggingface.co/jondurbin/airoboros-70b-3.3

static quants are available at https://huggingface.co/mradermacher/airoboros-70b-3.3-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-IQ2_M 24.2
GGUF i1-Q2_K 26.5 IQ3_XXS probably better
GGUF i1-IQ3_XXS 27.6 lower quality
GGUF i1-IQ3_XS 29.4
GGUF i1-IQ3_S 31.0 beats Q3_K*
GGUF i1-Q3_K_S 31.0 IQ3_XS probably better
GGUF i1-Q3_K_M 34.4 IQ3_S probably better
GGUF i1-Q3_K_L 37.2 IQ3_M probably better
GGUF i1-IQ4_XS 38.0
GGUF i1-Q4_0 40.2 fast, low quality
GGUF i1-Q4_K_S 40.4 optimal size/speed/quality
GGUF i1-Q4_K_M 42.6 fast, recommended
GGUF i1-Q5_K_S 48.8
GGUF i1-Q5_K_M 50.0
PART 1 PART 2 i1-Q6_K 58.0 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 hardware for calculating the imatrix for these quants.