mradermacher/Liberated-Qwen1.5-14B-GGUF

---

base_model: abacusai/Liberated-Qwen1.5-14B datasets:

• teknium/OpenHermes-2.5
• m-a-p/Code-Feedback
• m-a-p/CodeFeedback-Filtered-Instruction
• abacusai/SystemChat

language:

• en

library_name: transformers license: other license_link: https://huggingface.co/Qwen/Qwen1.5-72B/blob/main/LICENSE license_name: tongyi-qianwen quantized_by: mradermacher

---

About

static quants of https://huggingface.co/abacusai/Liberated-Qwen1.5-14B

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Liberated-Qwen1.5-14B-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	Q2_K	6.0
GGUF	Q3K_S	6.9
GGUF	Q3K_M	7.5	lower quality
GGUF	Q3K_L	7.9
GGUF	IQ4_XS	8.0
GGUF	Q404_4	8.3	fast on arm, low quality
GGUF	Q4K_S	8.7	fast, recommended
GGUF	Q4K_M	9.3	fast, recommended
GGUF	Q5K_S	10.1
GGUF	Q5K_M	10.6
GGUF	Q6_K	12.4	very good quality
GGUF	Q8_0	15.2	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. 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.