File size: 3,190 Bytes
199f07c 1887202 199f07c 94bc9d4 dae1ab1 b97b1bb 199f07c b97b1bb 199f07c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
---
datasets:
- tiiuae/falcon-refinedweb
- EleutherAI/pile
- meta-math/MetaMathQA
exported_from: deepnight-research/Saily_220B
language:
- en
library_name: transformers
license: llama2
quantized_by: mradermacher
---
## About
static quants of https://huggingface.co/deepnight-research/Saily_220B
<!-- provided-files -->
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](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q2_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q2_K.gguf.part2of2) | Q2_K | 76.9 | |
| [PART 1](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.IQ3_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.IQ3_S.gguf.part2of2) | IQ3_S | 90.4 | beats Q3_K* |
| [PART 1](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q3_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q3_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q3_K_M.gguf.part3of3) | Q3_K_M | 100.6 | lower quality |
| [PART 1](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q4_K_S.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q4_K_S.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q4_K_S.gguf.part3of3) | Q4_K_S | 118.6 | fast, recommended |
| [P1](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q8_0.gguf.part1of5) [P2](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q8_0.gguf.part2of5) [P3](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q8_0.gguf.part3of5) [P4](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q8_0.gguf.part4of5) [P5](https://huggingface.co/mradermacher/Saily_220B-GGUF/resolve/main/Saily_220B.Q8_0.gguf.part5of5) | Q8_0 | 221.8 | 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
## Thanks
I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.
<!-- end -->
|