Swallow-7b-hf-GGUF / README.md
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metadata
base_model: tokyotech-llm/Swallow-7b-hf
language:
  - en
  - ja
library_name: transformers
license: llama2
model_type: llama
quantized_by: mradermacher

About

static quants of https://huggingface.co/tokyotech-llm/Swallow-7b-hf

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Swallow-7b-hf-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 2.7
GGUF IQ3_XS 3.0
GGUF IQ3_S 3.1 beats Q3_K*
GGUF Q3_K_S 3.1
GGUF IQ3_M 3.3
GGUF Q3_K_M 3.5 lower quality
GGUF Q3_K_L 3.8
GGUF IQ4_XS 3.8
GGUF Q4_K_S 4.0 fast, recommended
GGUF Q4_K_M 4.2 fast, recommended
GGUF Q5_K_S 4.8
GGUF Q5_K_M 5.0
GGUF Q6_K 5.7 very good quality
GGUF Q8_0 7.4 fast, best quality
GGUF f16 13.8 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.