Edit model card

About

weighted/imatrix quants of https://huggingface.co/cognitivecomputations/Samantha-1.11-70b

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 15.0 for the desperate
GGUF i1-IQ1_M 16.4 mostly desperate
GGUF i1-IQ2_XXS 18.7
GGUF i1-IQ2_XS 20.8
GGUF i1-IQ2_S 21.8
GGUF i1-IQ2_M 23.7
GGUF i1-Q2_K 25.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 27.4 lower quality
GGUF i1-IQ3_XS 28.6
GGUF i1-Q3_K_XS 28.7
GGUF i1-IQ3_S 30.3 beats Q3_K*
GGUF i1-Q3_K_S 30.3 IQ3_XS probably better
GGUF i1-IQ3_M 31.4
GGUF i1-Q3_K_M 33.7 IQ3_S probably better
GGUF i1-Q3_K_L 36.6 IQ3_M probably better
GGUF i1-IQ4_XS 37.2
GGUF i1-IQ4_NL 39.4 prefer IQ4_XS
GGUF i1-Q4_0 39.4 fast, low quality
GGUF i1-Q4_K_S 39.7 optimal size/speed/quality
GGUF i1-Q4_K_M 41.8 fast, recommended
GGUF i1-Q5_K_S 47.9
GGUF i1-Q5_K_M 49.2
PART 1 PART 2 i1-Q6_K 57.0 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
500
GGUF
Model size
69B params
Architecture
llama
+4
Unable to determine this model’s pipeline type. Check the docs .

Quantized from

Dataset used to train mradermacher/Samantha-1.11-70b-i1-GGUF