base_model: nvidia/NFT-32B
datasets:
- BytedTsinghua-SIA/DAPO-Math-17k
language:
- en
library_name: transformers
license: other
license_link: https://huggingface.co/nvidia/NFT-32B/blob/main/LICENSE
license_name: nvidia-non-commercial-license
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- nvidia
- math
- reasoning
- post-training
- qwen
About
static quants of https://huggingface.co/nvidia/NFT-32B
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 | 12.4 |
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.