base_model: Dorian2B/Vera-1.0-Preview
language:
- fr
- en
- es
- it
- pl
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- French
- LLM
- 11B
- General
- llama-cpp
About
static quants of https://huggingface.co/Dorian2B/Vera-1.0-Preview
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Vera-1.0-Preview-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 | 4.3 | |
| GGUF | Q3_K_S | 5.0 | |
| GGUF | Q3_K_M | 5.5 | lower quality |
| GGUF | Q3_K_L | 6.0 | |
| GGUF | IQ4_XS | 6.2 | |
| GGUF | Q4_K_S | 6.5 | fast, recommended |
| GGUF | Q4_K_M | 6.8 | fast, recommended |
| GGUF | Q5_K_S | 7.8 | |
| GGUF | Q5_K_M | 8.0 | |
| GGUF | Q6_K | 9.3 | very good quality |
| GGUF | Q8_0 | 12.0 | 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.