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metadata
base_model: MarsupialAI/Yeet_51b_200k
language:
  - en
library_name: transformers
license: other
license_name: yi-other
no_imatrix: 'IQ3_XXS GGML_ASSERT: llama.cpp/ggml-quants.c:11239: grid_index >= 0'
quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/MarsupialAI/Yeet_51b_200k

No more quants forthcoming, as llama.cpp crashes.

static quants are available at https://huggingface.co/mradermacher/Yeet_51b_200k-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-Q2_K 19.6 IQ3_XXS probably better
GGUF i1-Q3_K_S 22.8 IQ3_XS probably better
GGUF i1-Q3_K_M 25.3 IQ3_S probably better
GGUF i1-Q3_K_L 27.6 IQ3_M probably better
GGUF i1-Q4_0 29.6 fast, low quality
GGUF i1-Q4_K_S 29.7 optimal size/speed/quality
GGUF i1-Q4_K_M 31.3 fast, recommended
GGUF i1-Q5_K_S 35.9
GGUF i1-Q5_K_M 36.8
GGUF i1-Q6_K 42.6 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.