mradermacher's picture
auto-patch README.md
a84dfd2 verified
metadata
base_model: Delta-Vector/SD-Prompter-1.5B-V0.1
datasets:
  - NewEden/CivitAI-SD-Prompts
language:
  - en
library_name: transformers
license: agpl-3.0
quantized_by: mradermacher
tags:
  - chat

About

static quants of https://huggingface.co/Delta-Vector/SD-Prompter-1.5B-V0.1

weighted/imatrix quants are available at https://huggingface.co/mradermacher/SD-Prompter-1.5B-V0.1-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 0.8
GGUF Q3_K_S 0.9
GGUF Q3_K_M 0.9 lower quality
GGUF Q3_K_L 1.0
GGUF IQ4_XS 1.0
GGUF Q4_0_4_4 1.0 fast on arm, low quality
GGUF Q4_K_S 1.0 fast, recommended
GGUF Q4_K_M 1.1 fast, recommended
GGUF Q5_K_S 1.2
GGUF Q5_K_M 1.2
GGUF Q6_K 1.4 very good quality
GGUF Q8_0 1.7 fast, best quality
GGUF f16 3.2 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.