mradermacher/FastApply-1.5B-v1.0-GGUF

---

base_model: Kortix/FastApply-1.5B-v1.0 language:

• en

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

• text-generation-inference
• transformers
• unsloth
• qwen2
• trl
• sft
• fast-apply
• instant-apply

---

About

static quants of https://huggingface.co/Kortix/FastApply-1.5B-v1.0

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	0.8
GGUF	Q3K_S	0.9
GGUF	Q3K_M	0.9	lower quality
GGUF	Q3K_L	1.0
GGUF	IQ4_XS	1.0
GGUF	Q4K_S	1.0	fast, recommended
GGUF	Q4K_M	1.1	fast, recommended
GGUF	Q5K_S	1.2
GGUF	Q5K_M	1.2
GGUF	Q6_K	1.4	very good quality
GGUF	Q8_0	1.7	fast, best quality
GGUF	f16	3.2	16 bpw, overkill

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.