Edit model card

About

weighted/imatrix quants of https://huggingface.co/CausalLM/34b-beta

static quants are available at https://huggingface.co/mradermacher/34b-beta-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 i1-IQ1_S 7.6 for the desperate
GGUF i1-IQ1_M 8.3 mostly desperate
GGUF i1-IQ2_XXS 9.4
GGUF i1-IQ2_XS 10.4
GGUF i1-IQ2_S 11.0
GGUF i1-IQ2_M 11.9
GGUF i1-Q2_K 12.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 13.4 lower quality
GGUF i1-IQ3_XS 14.3
GGUF i1-Q3_K_S 15.1 IQ3_XS probably better
GGUF i1-IQ3_S 15.1 beats Q3_K*
GGUF i1-IQ3_M 15.7
GGUF i1-Q3_K_M 16.8 IQ3_S probably better
GGUF i1-Q3_K_L 18.2 IQ3_M probably better
GGUF i1-IQ4_XS 18.6
GGUF i1-Q4_0 19.6 fast, low quality
GGUF i1-Q4_K_S 19.7 optimal size/speed/quality
GGUF i1-Q4_K_M 20.8 fast, recommended
GGUF i1-Q5_K_S 23.8
GGUF i1-Q5_K_M 24.4
GGUF i1-Q6_K 28.3 practically like static Q6_K

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
230
GGUF
Model size
34.4B params
Architecture
llama

1-bit

2-bit

3-bit

4-bit

5-bit

6-bit

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

Model tree for mradermacher/34b-beta-i1-GGUF

Base model

CausalLM/34b-beta
Quantized
(4)
this model