base_model: lightblue/DeepSeek-R1-Distill-Qwen-7B-Multilingual
datasets:
- lightblue/reasoning-multilingual-R1-Llama-70B-train
language:
- am
- ar
- bn
- zh
- cs
- nl
- en
- fr
- de
- el
- ha
- he
- hi
- id
- it
- ja
- jv
- km
- ko
- lo
- ms
- mr
- fa
- pl
- pt
- ro
- ru
- es
- sw
- sv
- tl
- ta
- te
- th
- tr
- uk
- ur
- vi
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- reasoning
About
static quants of https://huggingface.co/lightblue/DeepSeek-R1-Distill-Qwen-7B-Multilingual
weighted/imatrix quants are available at https://huggingface.co/mradermacher/DeepSeek-R1-Distill-Qwen-7B-Multilingual-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 | 3.1 | |
| GGUF | Q3_K_S | 3.6 | |
| GGUF | Q3_K_M | 3.9 | lower quality |
| GGUF | Q3_K_L | 4.2 | |
| GGUF | IQ4_XS | 4.4 | |
| GGUF | Q4_K_S | 4.6 | fast, recommended |
| GGUF | Q4_K_M | 4.8 | fast, recommended |
| GGUF | Q5_K_S | 5.4 | |
| GGUF | Q5_K_M | 5.5 | |
| GGUF | Q6_K | 6.4 | very good quality |
| GGUF | Q8_0 | 8.2 | fast, best quality |
| GGUF | f16 | 15.3 | 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.