mradermacher/granite-8b-code-base-GGUF

---

base_model: ibm-granite/granite-8b-code-base-4k datasets:

• codeparrot/github-code-clean
• bigcode/starcoderdata
• open-web-math/open-web-math
• math-ai/StackMathQA

language:

• en

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

• code
• granite

---

About

static quants of https://huggingface.co/ibm-granite/granite-8b-code-base-4k

weighted/imatrix quants are available at https://huggingface.co/mradermacher/granite-8b-code-base-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	3.2
GGUF	IQ3_XS	3.5
GGUF	Q3K_S	3.6
GGUF	IQ3S	3.7	beats Q3K*
GGUF	IQ3_M	3.8
GGUF	Q3K_M	4.0	lower quality
GGUF	Q3K_L	4.4
GGUF	IQ4_XS	4.5
GGUF	Q4K_S	4.7	fast, recommended
GGUF	Q4K_M	5.0	fast, recommended
GGUF	Q5K_S	5.7
GGUF	Q5K_M	5.8
GGUF	Q6_K	6.7	very good quality
GGUF	Q8_0	8.7	fast, best quality
GGUF	f16	16.2	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.