mradermacher/DeepSeek-R1-Distill-Qwen-14B-Uncensored-GGUF

---

base_model: nicoboss/DeepSeek-R1-Distill-Qwen-14B-Uncensored datasets:

• Guilherme34/uncensor

language:

• en

library_name: transformers license: mit quantized_by: mradermacher tags:

• generatedfromtrainer

---

About

static quants of https://huggingface.co/nicoboss/DeepSeek-R1-Distill-Qwen-14B-Uncensored

weighted/imatrix quants are available at https://huggingface.co/mradermacher/DeepSeek-R1-Distill-Qwen-14B-Uncensored-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	Q3K_S	6.8
GGUF	Q3K_M	7.4	lower quality
GGUF	Q3K_L	8.0
GGUF	IQ4_XS	8.3
GGUF	Q4K_S	8.7	fast, recommended
GGUF	Q4K_M	9.1	fast, recommended
GGUF	Q5K_S	10.4
GGUF	Q5K_M	10.6
GGUF	Q6_K	12.2	very good quality
GGUF	Q8_0	15.8	fast, best quality

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

!image.png

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.