Transformers
GGUF
English
Korean
Not-For-All-Audiences
Inference Endpoints
Edit model card

About

weighted/imatrix quants of https://huggingface.co/maywell/PiVoT-0.1-Evil-a

static quants are available at https://huggingface.co/mradermacher/PiVoT-0.1-Evil-a-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 1.7 for the desperate
GGUF i1-IQ1_M 1.9 mostly desperate
GGUF i1-IQ2_XXS 2.1
GGUF i1-IQ2_XS 2.3
GGUF i1-IQ2_S 2.4
GGUF i1-IQ2_M 2.6
GGUF i1-Q2_K 2.8 IQ3_XXS probably better
GGUF i1-IQ3_XXS 2.9 lower quality
GGUF i1-IQ3_XS 3.1
GGUF i1-Q3_K_S 3.3 IQ3_XS probably better
GGUF i1-IQ3_S 3.3 beats Q3_K*
GGUF i1-IQ3_M 3.4
GGUF i1-Q3_K_M 3.6 IQ3_S probably better
GGUF i1-Q3_K_L 3.9 IQ3_M probably better
GGUF i1-IQ4_XS 4.0
GGUF i1-Q4_0 4.2 fast, low quality
GGUF i1-Q4_K_S 4.2 optimal size/speed/quality
GGUF i1-Q4_K_M 4.5 fast, recommended
GGUF i1-Q5_K_S 5.1
GGUF i1-Q5_K_M 5.2
GGUF i1-Q6_K 6.0 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.

Downloads last month
381
GGUF
+3
Unable to determine this model’s pipeline type. Check the docs .

Quantized from

Datasets used to train mradermacher/PiVoT-0.1-Evil-a-i1-GGUF