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

base_model	datasets	language	library_name	license	mradermacher	quantized_by	tags
OpenGVLab/InternVL2_5-1B	HuggingFaceFV/finevideo	multilingual	transformers	mit	readme_rev 1	mradermacher	internvl custom_code

About

weighted/imatrix quants of https://huggingface.co/OpenGVLab/InternVL2_5-1B

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

static quants are available at https://huggingface.co/mradermacher/InternVL2_5-1B-GGUF

This is a vision model - mmproj files (if any) will be under files

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-IQ2_XS	0.5
GGUF	i1-IQ3_XS	0.5
GGUF	i1-IQ4_XS	0.5
GGUF	i1-Q4_K_M	0.6	fast, recommended
GGUF	i1-Q5_K_M	0.6
GGUF	i1-Q6_K	0.7	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.