mradermacher/mistral-7b-grok-GGUF

---

base_model: HuggingFaceH4/mistral-7b-grok datasets:

• HuggingFaceH4/grok-conversation-harmless
• HuggingFaceH4/ultrachat_200k

language:

• en

library_name: transformers license: apache-2.0 quantized_by: mradermacher tags:

• alignment-handbook
• generatedfromtrainer

---

About

static quants of https://huggingface.co/HuggingFaceH4/mistral-7b-grok

weighted/imatrix quants are available at https://huggingface.co/mradermacher/mistral-7b-grok-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	3.0
GGUF	IQ3_XS	3.3
GGUF	Q3K_S	3.4
GGUF	IQ3S	3.4	beats Q3K*
GGUF	IQ3_M	3.5
GGUF	Q3K_M	3.8	lower quality
GGUF	Q3K_L	4.1
GGUF	IQ4_XS	4.2
GGUF	Q404_4	4.2	fast on arm, low quality
GGUF	Q4K_S	4.4	fast, recommended
GGUF	Q4K_M	4.6	fast, recommended
GGUF	Q5K_S	5.3
GGUF	Q5K_M	5.4
GGUF	Q6_K	6.2	very good quality
GGUF	Q8_0	7.9	fast, best quality
GGUF	f16	14.6	16 bpw, overkill

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.