base_model: AI-MO/NuminaMath-72B-TIR
datasets:
- AI-MO/NuminaMath-TIR
language:
- en
library_name: transformers
license: other
license_name: tongyi-qianwen
quantized_by: mradermacher
tags:
- alignment-handbook
- generated_from_trainer
- math
- aimo
About
weighted/imatrix quants of https://huggingface.co/AI-MO/NuminaMath-72B-TIR
static quants are available at https://huggingface.co/mradermacher/NuminaMath-72B-TIR-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-IQ1_S | 22.8 | for the desperate |
| GGUF | i1-IQ1_M | 23.8 | mostly desperate |
| GGUF | i1-IQ2_XXS | 25.6 | |
| GGUF | i1-IQ2_XS | 27.2 | |
| GGUF | i1-IQ2_S | 28.0 | |
| GGUF | i1-IQ2_M | 29.4 | |
| GGUF | i1-Q2_K_S | 29.7 | very low quality |
| GGUF | i1-Q2_K | 29.9 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 31.9 | lower quality |
| GGUF | i1-Q3_K_S | 34.6 | IQ3_XS probably better |
| GGUF | i1-IQ3_M | 35.6 | |
| GGUF | i1-Q3_K_M | 37.8 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 39.6 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 39.8 | |
| GGUF | i1-Q4_K_S | 44.0 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 47.5 | fast, recommended |
| PART 1 PART 2 | i1-Q5_K_S | 51.5 | |
| PART 1 PART 2 | i1-Q5_K_M | 54.5 | |
| PART 1 PART 2 | i1-Q6_K | 64.4 | 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.