HamzahLMV2-1B-GGUF/README.md

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

base_model	datasets	language	library_name	license	quantized_by	tags
XeTute/HamzahLMV2-1B	XeTute/Eastern-Alpaca-14k XeTute/Medic-Thoughts-16k XeTute/iloveuser-1k vicgalle/alpaca-gpt4 stas/openwebtext-10k Magpie-Align/Magpie-Reasoning-V2-250K-CoT-QwQ Magpie-Align/Magpie-Reasoning-V1-150K-CoT-QwQ	en zh pt it fr de hi th	transformers	llama3.2	mradermacher	rp roleplay thinking thoughts reasoning multilingual

About

static quants of https://huggingface.co/XeTute/HamzahLMV2-1B

weighted/imatrix quants are available at https://huggingface.co/mradermacher/HamzahLMV2-1B-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	0.8
GGUF	Q3_K_S	0.9
GGUF	Q3_K_M	0.9	lower quality
GGUF	Q3_K_L	0.9
GGUF	IQ4_XS	1.0
GGUF	Q4_K_S	1.0	fast, recommended
GGUF	Q4_K_M	1.1	fast, recommended
GGUF	Q5_K_S	1.2
GGUF	Q5_K_M	1.2
GGUF	Q6_K	1.3	very good quality
GGUF	Q8_0	1.7	fast, best quality
GGUF	f16	3.1	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.