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metadata
base_model: Epiculous/Crimson_Dawn-v0.2
datasets:
  - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
  - anthracite-org/stheno-filtered-v1.1
  - PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
  - Gryphe/Sonnet3.5-Charcard-Roleplay
  - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
  - anthracite-org/kalo-opus-instruct-22k-no-refusal
  - anthracite-org/nopm_claude_writing_fixed
  - anthracite-org/kalo_opus_misc_240827
language:
  - en
  - fr
  - de
  - es
  - it
  - pt
  - ru
  - zh
  - ja
library_name: transformers
license: apache-2.0
quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/Epiculous/Crimson_Dawn-v0.2

static quants are available at https://huggingface.co/mradermacher/Crimson_Dawn-v0.2-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_M 3.3 mostly desperate
GGUF i1-IQ2_M 4.5
GGUF i1-Q2_K 4.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 5.0 lower quality
GGUF i1-Q3_K_S 5.6 IQ3_XS probably better
GGUF i1-IQ3_M 5.8
GGUF i1-Q3_K_M 6.2 IQ3_S probably better
GGUF i1-IQ4_XS 6.8
GGUF i1-Q4_K_S 7.2 optimal size/speed/quality
GGUF i1-Q4_K_M 7.6 fast, recommended
GGUF i1-Q6_K 10.2 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.