base_model: mlabonne/Meta-Llama-3-120B-Instruct
language:
- en
library_name: transformers
license: other
quantized_by: mradermacher
tags:
- merge
- mergekit
- lazymergekit
About
weighted/imatrix quants of https://huggingface.co/mlabonne/Meta-Llama-3-120B-Instruct
static quants are available at https://huggingface.co/mradermacher/Meta-Llama-3-120B-Instruct-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-IQ2_M | 41.4 | |
GGUF | i1-Q2_K | 45.2 | IQ3_XXS probably better |
GGUF | i1-IQ3_XXS | 47.1 | lower quality |
PART 1 PART 2 | i1-IQ3_XS | 50.3 | |
PART 1 PART 2 | i1-Q3_K_S | 52.9 | IQ3_XS probably better |
PART 1 PART 2 | i1-IQ3_S | 53.1 | beats Q3_K* |
PART 1 PART 2 | i1-IQ3_M | 54.8 | |
PART 1 PART 2 | i1-Q3_K_M | 58.9 | IQ3_S probably better |
PART 1 PART 2 | i1-Q3_K_L | 64.1 | IQ3_M probably better |
PART 1 PART 2 | i1-IQ4_XS | 65.4 | |
PART 1 PART 2 | i1-Q4_0 | 69.2 | fast, low quality |
PART 1 PART 2 | i1-Q4_K_S | 69.5 | optimal size/speed/quality |
PART 1 PART 2 | i1-Q4_K_M | 73.3 | fast, recommended |
PART 1 PART 2 | i1-Q5_K_S | 84.1 | |
PART 1 PART 2 | i1-Q5_K_M | 86.3 | |
PART 1 PART 2 PART 3 | i1-Q6_K | 100.1 | practically like static Q6_K |
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
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.