base_model: mgoin/Nemotron-4-340B-Base-hf
language:
- en
library_name: transformers
license: other
license_link: >-
https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
license_name: nvidia-open-model-license
quantized_by: mradermacher
tags:
- vllm
About
static quants of https://huggingface.co/mgoin/Nemotron-4-340B-Base-hf
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Nemotron-4-340B-Base-hf-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 |
|---|---|---|---|
| PART 1 PART 2 PART 3 | Q2_K | 131.6 | |
| PART 1 PART 2 PART 3 PART 4 | Q3_K_S | 148.5 | |
| PART 1 PART 2 PART 3 PART 4 | Q3_K_M | 171.6 | lower quality |
| PART 1 PART 2 PART 3 PART 4 | Q3_K_L | 191.3 | |
| PART 1 PART 2 PART 3 PART 4 | Q4_K_S | 195.2 | fast, recommended |
| P1 P2 P3 P4 P5 | Q4_K_M | 210.3 | fast, recommended |
| P1 P2 P3 P4 P5 | Q5_K_S | 235.2 | |
| P1 P2 P3 P4 P5 | Q5_K_M | 244.1 | |
| P1 P2 P3 P4 P5 P6 | Q6_K | 279.9 | very good quality |
| P1 P2 P3 P4 P5 P6 P7 P8 | Q8_0 | 362.5 | fast, best quality |
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.