base_model: empero-ai/openNemo-9B-abliterated
datasets:
- nvidia/Nemotron-Post-Training-Dataset-v1
- nvidia/Nemotron-Post-Training-Dataset-v2
- nvidia/Nemotron-Pretraining-Dataset-sample
- nvidia/Nemotron-CC-v2
- nvidia/Nemotron-CC-Math-v1
- nvidia/Nemotron-Pretraining-SFT-v1
language: - en
- es
- fr
- de
- it
- ja
library_name: transformers
license: other
license_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
license_name: nvidia-open-model-license
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags: - nvidia
- pytorch
- abliteration
- uncensored
About
weighted/imatrix quants of https://huggingface.co/empero-ai/openNemo-9B-abliterated
For a convenient overview and download list, visit our model page for this model.
static quants are available at https://huggingface.co/mradermacher/openNemo-9B-abliterated-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 | imatrix | 0.1 | imatrix file (for creating your own quants) |
| GGUF | i1-IQ1_S | 4.9 | for the desperate |
| GGUF | i1-IQ1_M | 5.0 | mostly desperate |
| GGUF | i1-IQ2_XXS | 5.0 | |
| GGUF | i1-IQ2_XS | 5.0 | |
| GGUF | i1-IQ2_S | 5.1 | |
| GGUF | i1-IQ2_M | 5.1 | |
| GGUF | i1-Q2_K | 5.1 | IQ3_XXS probably better |
| GGUF | i1-Q2_K_S | 5.2 | very low quality |
| GGUF | i1-IQ3_XXS | 5.2 | lower quality |
| GGUF | i1-IQ3_S | 5.2 | beats Q3_K* |
| GGUF | i1-IQ3_XS | 5.2 | |
| GGUF | i1-Q3_K_S | 5.2 | IQ3_XS probably better |
| GGUF | i1-IQ3_M | 5.3 | |
| GGUF | i1-IQ4_XS | 5.4 | |
| GGUF | i1-IQ4_NL | 5.4 | prefer IQ4_XS |
| GGUF | i1-Q4_0 | 5.4 | fast, low quality |
| GGUF | i1-Q3_K_M | 5.5 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 5.6 | IQ3_M probably better |
| GGUF | i1-Q4_1 | 5.9 | |
| GGUF | i1-Q4_K_S | 6.3 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 6.6 | fast, recommended |
| GGUF | i1-Q5_K_S | 6.9 | |
| GGUF | i1-Q5_K_M | 7.2 | |
| GGUF | i1-Q6_K | 9.2 | practically like static Q6_K |
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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.