LexGPT-V1-GGUF/README.md

base_model, datasets, language, library_name, license, quantized_by

base_model	datasets	language	library_name	license	quantized_by
lex-hue/LexGPT-V1	TIGER-Lab/MathInstruct LDJnr/Capybara openchat/openchat_sharegpt4_dataset imone/OpenOrca_FLAN Open-Orca/OpenOrca Intel/orca_dpo_pairs LDJnr/LessWrong-Amplify-Instruct LDJnr/Pure-Dove LDJnr/Verified-Camel tiedong/goat glaiveai/glaive-code-assistant OpenAssistant/oasst_top1_2023-08-25	en de	transformers	mit	mradermacher

About

static quants of https://huggingface.co/lex-hue/LexGPT-V1

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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	2.8
GGUF	Q3_K_S	3.3
GGUF	Q3_K_M	3.6	lower quality
GGUF	Q3_K_L	3.9
GGUF	IQ4_XS	4.0
GGUF	Q4_K_S	4.2	fast, recommended
GGUF	Q4_K_M	4.5	fast, recommended
GGUF	Q5_K_S	5.1
GGUF	Q5_K_M	5.2
GGUF	Q6_K	6.0	very good quality
GGUF	Q8_0	7.8	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):

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.