mradermacher/gpt-oss-20b-trendyol-instruct-data-GGUF

---

base_model: mjolnirthors/gpt-oss-20b-trendyol-instruct-data language:

• en

library_name: transformers model_name: gpt-oss-20b-trendyol-instruct-data mradermacher: readme_rev: 1 quantized_by: mradermacher tags:

• generatedfromtrainer
• sft
• trl

---

About

static quants of https://huggingface.co/mjolnirthors/gpt-oss-20b-trendyol-instruct-data

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/gpt-oss-20b-trendyol-instruct-data-i1-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	Q3K_S	12.2
GGUF	Q2_K	12.2
GGUF	IQ4_XS	12.3
GGUF	Q3K_M	13.0	lower quality
GGUF	Q3K_L	13.4
GGUF	Q4K_S	14.8	fast, recommended
GGUF	Q4K_M	15.9	fast, recommended
GGUF	Q5K_S	16.0
GGUF	Q5K_M	17.0
GGUF	Q6_K	22.3	very good quality
GGUF	Q8_0	22.4	fast, best quality

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.