miqu-1-103b-GGUF / README.md
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metadata
base_model:
  - 152334H/miqu-1-70b-sf
language:
  - en
library_name: transformers
quantized_by: mradermacher
tags:
  - mergekit
  - merge

About

static quants of https://huggingface.co/wolfram/miqu-1-103b

weighted/imatrix quants available at https://huggingface.co/mradermacher/miqu-1-103b-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 38.2
GGUF IQ3_XS 42.4
GGUF Q3_K_S 44.8
PART 1 PART 2 Q3_K_M 49.9 lower quality
PART 1 PART 2 Q3_K_L 54.4
PART 1 PART 2 Q4_K_S 58.9 fast, medium quality
PART 1 PART 2 Q4_K_M 62.2 fast, medium quality
PART 1 PART 2 Q5_K_S 71.3
PART 1 PART 2 Q5_K_M 73.2
PART 1 PART 2 Q6_K 85.0 very good quality
PART 1 PART 2 PART 3 Q8_0 109.9 fast, best quality

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png