Edit model card

About

static quants of https://huggingface.co/MTSAIR/MultiVerse_70B

weighted/imatrix quants are available at https://huggingface.co/mradermacher/MultiVerse_70B-i1-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 Q2_K 28.6
GGUF IQ3_XS 31.5
GGUF IQ3_S 33.1 beats Q3_K*
GGUF Q3_K_S 33.1
GGUF IQ3_M 34.8
GGUF Q3_K_M 36.8 lower quality
GGUF Q3_K_L 40.1
GGUF IQ4_XS 40.7
GGUF Q4_K_S 42.9 fast, recommended
GGUF Q4_K_M 45.3 fast, recommended
PART 1 PART 2 Q5_K_S 51.5
PART 1 PART 2 Q5_K_M 52.9
PART 1 PART 2 Q6_K 60.9 very good quality
PART 1 PART 2 Q8_0 78.1 fast, best quality

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
178
GGUF
Model size
72.3B params
Architecture
llama

2-bit

3-bit

4-bit

Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for mradermacher/MultiVerse_70B-GGUF

Quantized
(2)
this model