base_model: ConicCat/Apriel-R1PV.2-Thinking
datasets:
- Undi95/R1-RP-ShareGPT3
- PJMixers-Dev/Gryphe-Aesir-RPG-Charcards-Opus-Mixed-split-v3-0324
language:
- en
library_name: transformers
mradermacher:
readme_rev: 1
quantized_by: mradermacher
About
static quants of https://huggingface.co/ConicCat/Apriel-R1PV.2-Thinking
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Apriel-R1PV.2-Thinking-i1-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 | Q2_K | 5.9 | |
| GGUF | Q3_K_S | 6.8 | |
| GGUF | Q3_K_M | 7.5 | lower quality |
| GGUF | Q3_K_L | 8.1 | |
| GGUF | IQ4_XS | 8.4 | |
| GGUF | Q4_K_S | 8.8 | fast, recommended |
| GGUF | Q4_K_M | 9.2 | fast, recommended |
| GGUF | Q5_K_S | 10.5 | |
| GGUF | Q5_K_M | 10.8 | |
| GGUF | Q6_K | 12.4 | very good quality |
| GGUF | Q8_0 | 16.0 | fast, best quality |
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.