base_model: ymcki/gemma-2-2b-jpn-it-abliterated-18-ORPO
datasets:
- mlabonne/orpo-dpo-mix-40k
language: - multilingual
library_name: transformers
license: gemma
license_link: https://ai.google.dev/gemma/terms
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags: - nlp
- code
About
static quants of https://huggingface.co/ymcki/gemma-2-2b-jpn-it-abliterated-18-ORPO
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/gemma-2-2b-jpn-it-abliterated-18-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 | Q2_K | 1.3 | |
| GGUF | Q3_K_S | 1.5 | |
| GGUF | Q3_K_M | 1.6 | lower quality |
| GGUF | Q3_K_L | 1.7 | |
| GGUF | IQ4_XS | 1.7 | |
| GGUF | Q4_K_S | 1.7 | fast, recommended |
| GGUF | Q4_K_M | 1.8 | fast, recommended |
| GGUF | Q5_K_S | 2.0 | |
| GGUF | Q5_K_M | 2.0 | |
| GGUF | Q6_K | 2.3 | very good quality |
| GGUF | Q8_0 | 2.9 | fast, best quality |
| GGUF | f16 | 5.3 | 16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
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.