mradermacher's picture
auto-patch README.md
ac2fa99 verified
metadata
base_model: Weyaxi/Bagel-Hermes-2x34B
language:
  - en
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE
license_name: yi-license
quantized_by: mradermacher
tags:
  - yi
  - moe

About

weighted/imatrix quants of https://huggingface.co/Weyaxi/Bagel-Hermes-2x34B

static quants are available at https://huggingface.co/mradermacher/Bagel-Hermes-2x34B-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 12.9 for the desperate
GGUF i1-IQ1_M 14.2 mostly desperate
GGUF i1-IQ2_XXS 16.3
GGUF i1-IQ2_XS 18.1
GGUF i1-IQ2_S 18.8
GGUF i1-IQ2_M 20.5
GGUF i1-Q2_K 22.5 IQ3_XXS probably better
GGUF i1-IQ3_XXS 23.6 lower quality
GGUF i1-IQ3_XS 25.1
GGUF i1-Q3_K_S 26.4 IQ3_XS probably better
GGUF i1-IQ3_S 26.5 beats Q3_K*
GGUF i1-IQ3_M 27.2
GGUF i1-Q3_K_M 29.3 IQ3_S probably better
GGUF i1-Q3_K_L 31.9 IQ3_M probably better
GGUF i1-IQ4_XS 32.6
GGUF i1-Q4_0 34.6 fast, low quality
GGUF i1-Q4_K_S 34.7 optimal size/speed/quality
GGUF i1-Q4_K_M 36.8 fast, recommended
GGUF i1-Q5_K_S 42.0
GGUF i1-Q5_K_M 43.2
GGUF i1-Q6_K 50.0 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.