About

static quants of https://huggingface.co./mylesgoose/Llama-3.1-70B-Instruct-abliterated

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 26.5
GGUF IQ3_XS 29.4
GGUF IQ3_S 31.0 beats Q3_K*
GGUF Q3_K_S 31.0
GGUF IQ3_M 32.0
GGUF Q3_K_M 34.4 lower quality
GGUF Q3_K_L 37.2
GGUF IQ4_XS 38.4
GGUF Q4_K_S 40.4 fast, recommended
GGUF Q4_K_M 42.6 fast, recommended
GGUF Q5_K_S 48.8
GGUF Q5_K_M 50.0
PART 1 PART 2 Q6_K 58.0 very good quality
PART 1 PART 2 Q8_0 75.1 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.

Downloads last month
242
GGUF
Model size
70.6B params
Architecture
llama

2-bit

3-bit

4-bit

5-bit

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

Model tree for mradermacher/Llama-3.1-70B-Instruct-abliterated-GGUF

Quantized
(1)
this model