base_model: EleutherAI/deep-ignorance-unfiltered
datasets:
- EleutherAI/deep-ignorance-pretraining-mix
- EleutherAI/deep-ignorance-annealing-mix
language: - en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags: - pytorch
- causal-lm
- pythia
- safety
- unlearning
- data-filtering
- interpretability
- pretraining
- eleutherai
- gpt-neox
- wmdp
- cbrn
- tamper-resistance
- research
- model-suite
- 6.9b
- circuit-breaking
- knowledge-filtering
- open-weight
- biothreat
- safety-research
- model-diffing
- training-dynamics
About
static quants of https://huggingface.co/EleutherAI/deep-ignorance-unfiltered
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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 | 2.7 | |
| GGUF | Q3_K_S | 3.1 | |
| GGUF | Q3_K_M | 3.7 | lower quality |
| GGUF | IQ4_XS | 3.9 | |
| GGUF | Q3_K_L | 4.0 | |
| GGUF | Q4_K_S | 4.1 | fast, recommended |
| GGUF | Q4_K_M | 4.5 | fast, recommended |
| GGUF | Q5_K_S | 4.8 | |
| GGUF | Q5_K_M | 5.2 | |
| GGUF | Q6_K | 5.7 | very good quality |
| GGUF | Q8_0 | 7.4 | fast, best quality |
| GGUF | f16 | 13.8 | 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.