About

static quants of https://huggingface.co/LumiOpen/Poro-34B-chat

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Poro-34B-chat-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 13.5
GGUF IQ3_XS 15.2
GGUF IQ3_S 15.6 beats Q3_K*
GGUF Q3_K_S 15.6
GGUF IQ3_M 17.2
GGUF Q3_K_M 18.6 lower quality
GGUF IQ4_XS 19.2
GGUF Q3_K_L 20.3
GGUF Q4_K_S 20.3 fast, recommended
GGUF Q4_K_M 22.5 fast, recommended
GGUF Q5_K_S 24.4
GGUF Q5_K_M 26.2
GGUF Q6_K 28.9 very good quality
GGUF Q8_0 37.4 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.

Downloads last month
244
GGUF
Model size
35.1B params
Architecture
bloom

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for mradermacher/Poro-34B-chat-GGUF

Quantized
(3)
this model

Dataset used to train mradermacher/Poro-34B-chat-GGUF