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metadata
base_model: baichuan-inc/Baichuan2-7B-Chat
language:
  - en
  - zh
library_name: transformers
license_link: >-
  https://huggingface.co./baichuan-inc/Baichuan2-7B-Chat/blob/main/Community%20License%20for%20Baichuan2%20Model.pdf
license_name: baichuan2-community-license
quantized_by: mradermacher

About

static quants of https://huggingface.co./baichuan-inc/Baichuan2-7B-Chat

weighted/imatrix quants are available at https://huggingface.co./mradermacher/Baichuan2-7B-Chat-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 3.1
GGUF Q3_K_S 3.5
GGUF Q3_K_M 3.9 lower quality
GGUF Q3_K_L 4.2
GGUF IQ4_XS 4.3
GGUF Q4_0_4_4 4.5 fast on arm, low quality
GGUF Q4_K_S 4.5 fast, recommended
GGUF Q4_K_M 4.7 fast, recommended
GGUF Q5_K_S 5.3
GGUF Q5_K_M 5.5
GGUF Q6_K 6.3 very good quality
GGUF Q8_0 8.1 fast, best quality
GGUF f16 15.1 16 bpw, overkill

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.