Qwen3-Shining-Lucy-CODER-2.4B-e32-i1-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
DavidAU/Qwen3-Shining-Lucy-CODER-2.4B-e32	sequelbox/Celestia3-DeepSeek-R1-0528 sequelbox/Mitakihara-DeepSeek-R1-0528 sequelbox/Raiden-DeepSeek-R1	en	transformers	apache-2.0	readme_rev 1	mradermacher	merge programming code generation code coding coder chat code chat qwen qwen3 qwencoder esper esper-3 valiant valiant-labs qwen qwen-3 qwen-3-2.4b 2.4b reasoning code code-instruct python javascript dev-ops jenkins terraform scripting powershell azure aws gcp cloud problem-solving architect engineer developer creative analytical expert rationality conversational chat instruct shining-valiant shining-valiant-3 valiant valiant-labs qwen qwen-3 qwen-3-1.7b 1.7b reasoning code code-reasoning science science-reasoning physics biology chemistry earth-science astronomy machine-learning artificial-intelligence compsci computer-science information-theory ML-Ops math cuda deep-learning transformers agentic LLM neuromorphic self-improvement complex-systems cognition linguistics philosophy logic epistemology simulation game-theory knowledge-management creativity problem-solving architect engineer developer creative analytical expert rationality conversational chat instruct float32

About

weighted/imatrix quants of https://huggingface.co/DavidAU/Qwen3-Shining-Lucy-CODER-2.4B-e32

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

static quants are available at https://huggingface.co/mradermacher/Qwen3-Shining-Lucy-CODER-2.4B-e32-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	imatrix	0.1	imatrix file (for creating your own quants)
GGUF	i1-IQ1_S	0.8	for the desperate
GGUF	i1-IQ1_M	0.8	mostly desperate
GGUF	i1-IQ2_XXS	0.9
GGUF	i1-IQ2_XS	0.9
GGUF	i1-IQ2_S	1.0
GGUF	i1-IQ2_M	1.0
GGUF	i1-Q2_K_S	1.1	very low quality
GGUF	i1-IQ3_XXS	1.1	lower quality
GGUF	i1-Q2_K	1.1	IQ3_XXS probably better
GGUF	i1-IQ3_XS	1.2
GGUF	i1-IQ3_S	1.3	beats Q3_K*
GGUF	i1-Q3_K_S	1.3	IQ3_XS probably better
GGUF	i1-IQ3_M	1.3
GGUF	i1-Q3_K_M	1.4	IQ3_S probably better
GGUF	i1-Q3_K_L	1.5	IQ3_M probably better
GGUF	i1-IQ4_XS	1.5
GGUF	i1-IQ4_NL	1.6	prefer IQ4_XS
GGUF	i1-Q4_0	1.6	fast, low quality
GGUF	i1-Q4_K_S	1.6	optimal size/speed/quality
GGUF	i1-Q4_K_M	1.6	fast, recommended
GGUF	i1-Q4_1	1.7
GGUF	i1-Q5_K_S	1.8
GGUF	i1-Q5_K_M	1.9
GGUF	i1-Q6_K	2.1	practically like static Q6_K

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.