loggenix-moe-0.12B-A0.08B-e5-lr5e4-b16-3060-v2-finetuned-GGUF/README.md

base_model, datasets, language, library_name, license, mradermacher, quantized_by, tags

base_model	datasets	language	library_name	license	mradermacher	quantized_by	tags
kshitijthakkar/loggenix-moe-0.12B-A0.08B-e5-lr5e4-b16-3060-v2-finetuned	kshitijthakkar/loggenix-mc-oraca-agentinstruct-1m-v1	en	transformers	apache-2.0	readme_rev 1	mradermacher	qwen3 qwen3moe mixture-of-experts llm text-generation instruction-following agentic-ai tool-use low-resource edge-ai from-scratch causal-lm

About

static quants of https://huggingface.co/kshitijthakkar/loggenix-moe-0.12B-A0.08B-e5-lr5e4-b16-3060-v2-finetuned

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/loggenix-moe-0.12B-A0.08B-e5-lr5e4-b16-3060-v2-finetuned-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	0.2
GGUF	Q3_K_S	0.2
GGUF	Q3_K_M	0.2	lower quality
GGUF	Q3_K_L	0.2
GGUF	IQ4_XS	0.2
GGUF	Q4_K_S	0.2	fast, recommended
GGUF	Q4_K_M	0.2	fast, recommended
GGUF	Q5_K_S	0.2
GGUF	Q5_K_M	0.2
GGUF	Q6_K	0.2	very good quality
GGUF	Q8_0	0.2	fast, best quality
GGUF	f16	0.4	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.