mradermacher's picture
auto-patch README.md
5053ec2 verified
metadata
base_model: EpistemeAI/Athene-Phi-3.5-mini-instruct-orpo
language:
  - en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - llama
  - trl

About

static quants of https://huggingface.co/EpistemeAI/Athene-Phi-3.5-mini-instruct-orpo

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Athene-Phi-3.5-mini-instruct-orpo-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 IQ3_XS 1.7
GGUF IQ3_S 1.8 beats Q3_K*
GGUF IQ3_M 1.9
GGUF Q4_0_4_4 2.3 fast on arm, low quality
PART 1 PART 2 Q2_K 3.0
PART 1 PART 2 Q3_K_S 3.5
PART 1 PART 2 Q3_K_M 3.9 lower quality
PART 1 PART 2 Q3_K_L 4.2
PART 1 PART 2 IQ4_XS 4.3
PART 1 PART 2 Q4_K_S 4.5 fast, recommended
PART 1 PART 2 Q4_K_M 4.7 fast, recommended
PART 1 PART 2 Q5_K_S 5.4
PART 1 PART 2 Q5_K_M 5.5
PART 1 PART 2 Q6_K 6.4 very good quality
PART 1 PART 2 Q8_0 8.2 fast, best quality
PART 1 PART 2 f16 15.4 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.