base_model: yhavinga/Bor-1B
datasets:
- yhavinga/mc4_nl_cleaned
- Kalamazooter/GeminiPhiDutch
- euirim/goodwiki
- code-search-net/code_search_net
- codeparrot/github-code-clean
- Zyphra/Zyda-2
- uonlp/CulturaX
- OpenCoder-LLM/opc-fineweb-math-corpus
- OpenCoder-LLM/opc-fineweb-code-corpus
- teknium/OpenHermes-2.5
- yhavinga/Openhermes-2.5-dutch-46k
language:
- nl
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
About
static quants of https://huggingface.co/yhavinga/Bor-1B
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Bor-1B-v1-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 | 0.6 | |
| GGUF | Q3_K_S | 0.6 | |
| GGUF | Q3_K_M | 0.7 | lower quality |
| GGUF | Q3_K_L | 0.7 | |
| GGUF | IQ4_XS | 0.8 | |
| GGUF | Q4_K_S | 0.8 | fast, recommended |
| GGUF | Q4_K_M | 0.8 | fast, recommended |
| GGUF | Q5_K_S | 0.9 | |
| GGUF | Q5_K_M | 0.9 | |
| GGUF | Q6_K | 1.1 | very good quality |
| GGUF | Q8_0 | 1.4 | fast, best quality |
| GGUF | f16 | 2.5 | 16 bpw, overkill |
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.