mradermacher/Pelican1.0-VL-235B-A22B-FC-i1-GGUF

---

base_model: X-Humanoid/Pelican1.0-VL-235B-A22B-FC language:

• en

library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags:

• Physical AI
• embodied-ai
• multimodal-learning
• robotics

---

About

weighted/imatrix quants of https://huggingface.co/X-Humanoid/Pelican1.0-VL-235B-A22B-FC

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

static quants are available at https://huggingface.co/mradermacher/Pelican1.0-VL-235B-A22B-FC-GGUF

This is a vision model - mmproj files (if any) will be in the static repository.

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	0.6	imatrix file (for creating your own quants)
GGUF	i1-IQ1_S	48.0	for the desperate
GGUF	i1-IQ1_M	53.2	mostly desperate
GGUF	i1-IQ2_XXS	61.9
GGUF	i1-IQ2_XS	68.9
GGUF	i1-IQ2_S	70.3
GGUF	i1-IQ2_M	77.3
GGUF	i1-Q2K_S	79.9	very low quality
GGUF	i1-Q2K	85.8	IQ3XXS probably better
GGUF	i1-IQ3_XXS	90.5	lower quality
GGUF	i1-IQ3_XS	96.1
GGUF	i1-Q3KS	101.5	IQ3XS probably better
GGUF	i1-IQ3S	101.6	beats Q3K*
GGUF	i1-IQ3_M	103.2
GGUF	i1-Q3KM	112.5	IQ3S probably better
GGUF	i1-Q3KL	121.9	IQ3M probably better
GGUF	i1-IQ4_XS	125.4
GGUF	i1-Q4_0	133.2	fast, low quality
GGUF	i1-Q4K_S	133.8	optimal size/speed/quality
GGUF	i1-Q4K_M	142.3	fast, recommended
GGUF	i1-Q4_1	147.3
GGUF	i1-Q5K_S	162.0
GGUF	i1-Q5K_M	166.9
GGUF	i1-Q6K	193.1	practically like static Q6K

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

!image.png

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.