base_model: DebateLabKIT/Llama-3.3-Argunaut-1-70B-SPIN
datasets:
- DebateLabKIT/argdown_line-by-line
- DebateLabKIT/argument_mapping_dpo_pairs
- allenai/llama-3.1-tulu-3-70b-preference-mixture
language:
- en
library_name: transformers
model_name: Llama-3.3-Argunaut-1-70B-SPIN
quantized_by: mradermacher
tags:
- logic
- argumentation
- critical-thinking
- argument-mapping
- generated_from_trainer
- trl
- dpo
- spin
About
weighted/imatrix quants of https://huggingface.co./DebateLabKIT/Llama-3.3-Argunaut-1-70B-SPIN
static quants are available at https://huggingface.co./mradermacher/Llama-3.3-Argunaut-1-70B-SPIN-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 | i1-Q2_K | 26.5 | IQ3_XXS probably better |
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.