base_model, datasets, language, library_name, license, license_link, license_name, quantized_by

base_model	datasets	language	library_name	license	license_link	license_name	quantized_by
Telugu-LLM-Labs/Indic-gemma-2b-finetuned-sft-Navarasa-2.0	ravithejads/samvaad-hi-filtered Telugu-LLM-Labs/telugu_teknium_GPTeacher_general_instruct_filtered_romanized Telugu-LLM-Labs/telugu_alpaca_yahma_cleaned_filtered_romanized Telugu-LLM-Labs/sindhi_alpaca_yahma_cleaned_filtered Telugu-LLM-Labs/urdu_alpaca_yahma_cleaned_filtered Telugu-LLM-Labs/marathi_alpaca_yahma_cleaned_filtered Telugu-LLM-Labs/assamese_alpaca_yahma_cleaned_filtered Telugu-LLM-Labs/konkani_alpaca_yahma_cleaned_filtered Telugu-LLM-Labs/nepali_alpaca_yahma_cleaned_filtered abhinand/tamil-alpaca Tensoic/airoboros-3.2_kn Tensoic/gpt-teacher_kn VishnuPJ/Alpaca_Instruct_Malayalam Tensoic/Alpaca-Gujarati HydraIndicLM/punjabi_alpaca_52K HydraIndicLM/bengali_alpaca_dolly_67k OdiaGenAI/Odia_Alpaca_instructions_52k yahma/alpaca-cleaned	te en ta ml mr hi kn sd ne ur as gu bn pa or	transformers	other	https://ai.google.dev/gemma/terms	gemma-terms-of-use	mradermacher

About

weighted/imatrix quants of https://huggingface.co/Telugu-LLM-Labs/Indic-gemma-2b-finetuned-sft-Navarasa-2.0

static quants are available at https://huggingface.co/mradermacher/Indic-gemma-2b-finetuned-sft-Navarasa-2.0-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	i1-IQ1_S	0.9	for the desperate
GGUF	i1-IQ1_M	0.9	mostly desperate
GGUF	i1-IQ2_XXS	1.0
GGUF	i1-IQ2_XS	1.0
GGUF	i1-IQ2_S	1.1
GGUF	i1-IQ2_M	1.1
GGUF	i1-Q2_K_S	1.2	very low quality
GGUF	i1-IQ3_XXS	1.2	lower quality
GGUF	i1-Q2_K	1.3	IQ3_XXS probably better
GGUF	i1-IQ3_XS	1.3
GGUF	i1-Q3_K_S	1.4	IQ3_XS probably better
GGUF	i1-IQ3_S	1.4	beats Q3_K*
GGUF	i1-IQ3_M	1.4
GGUF	i1-Q3_K_M	1.5	IQ3_S probably better
GGUF	i1-Q3_K_L	1.6	IQ3_M probably better
GGUF	i1-IQ4_XS	1.6
GGUF	i1-Q4_0	1.7	fast, low quality
GGUF	i1-Q4_K_S	1.7	optimal size/speed/quality
GGUF	i1-Q4_K_M	1.7	fast, recommended
GGUF	i1-Q5_K_S	1.9
GGUF	i1-Q5_K_M	1.9
GGUF	i1-Q6_K	2.2	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.