File size: 3,237 Bytes
84e3837 6dc2008 84e3837 6dc2008 a875cdb 63fd687 6dc2008 41238ab 6dc2008 84e3837 6dc2008 a875cdb 6dc2008 a875cdb 84e3837 ea421ff 6dc2008 ea421ff 6dc2008 ea421ff a875cdb |
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 |
---
license: other
license_name: yi-license
license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE
tags:
- merge
- GGUF
- imatrix
- 2bit
---
# Kyllene-57B
[Kyllene-57B](/TeeZee/Kyllene-57B-v1.0) quantized to 2~3 bpw [GGUF](/TeeZee/Kyllene-57B-v1.0-GGUF/blob/main/Kyllene-57B-v1.0.q6_K.gguf)-GGUF
### Please ❤️like❤️/📧comment📧/💌mail me some anthrax spores💌 if you use these! The download ticker won't work on a repo like this, so there's no feedback. I'm not wasting my time, right?
#### NOTICE: I did not use the original file! I started with Q6_K (there was no Q8 and more precision for this would be absurd). There may well be problems with these quants but I'll eat my own entire ass if a 57B Q6_K (>6.5bpw) is the root of any of them. More suspect is how I produced the imatrix.
[imatrix included.](./Kyllene-57B-v1.0.q6_K.gguf.imatrix) generated from [a 900k text file, also included](./techmulcodetiny.utf8)
this file was made by concatenating most of the [default exllamav2 calibration data](https://github.com/turboderp/exllamav2/tree/master/conversion/standard_cal_data). a 900kb file of coherent text only, with some formatting and code but no endless broken html tags or nonsense. includes multilingual, for those deep layers.
artefact produced from:
```
$ cd exllamav2/conversion/standard_cal_data
$ cat technical.utf8 multilingual.utf8 code.utf8 tiny.utf8 > techmulcodetiny.utf8
```
where: [exllamav2/conversion/standard_cal_data](https://github.com/turboderp/exllamav2/tree/master/conversion/standard_cal_data) and [techmulcodetiny.utf8](./techmulcodetiny.utf8) produce a file that is used by imatrix for 560~ "chunks"
imatrix run with default sampling settings besides the dataset (i think? i increased the batch number and reduced the batch size so i could cram on more layers but the generation should have been the same in the end)
(someone tell me why I was wrong to run imatrix with -cb continuous batching. shame me.)
# Downloads (eventually)
under consideration:
- Q2_K_S (imat only but I think compatible with older things. I'm not very sure what this is. )
- Q2_K (should be strictly better than [the original](/TeeZee/Kyllene-57B-v1.0-GGUF/blob/main/Kyllene-57B-v1.0.q2_K.gguf) but this may be where my --allow-requantize comes to bite me, we'll see)
```upload in progress: (probably done by now)```
[IQ2_XS](./Kyllene-57B-v1.0.IQ2_XS.gguf/) 2.38 BPW `CUDA0 buffer size = 15941.43 MiB`
- This file only exists because I did the maths wrong (I was expecting it to be bigger), but I recall that 16GB GPUs exist and I may give it a go with stable diffusion
```upload scheduled in order: (big gpuboys just have to wait)```
[IQ2_M](./Kyllene-57B-v1.0.IQ2_M.gguf/) 2.7 BPW
- briefly existed before I [clobbered](http://catb.org/jargon/html/C/clobber.html) _(verb, transitory)_ it. It ~might~ will be back.
[IQ3_XXS](./Kyllene-57B-v1.0.IQ3_XXS.gguf/) 3.0<`size`<3.1 BPW
- 3090 enjoyers and their friends may want to run this with -nkvo and -ngl 100 ( no K/V offload 100 layers in koboldcpp). There are 101 layers and the last one becomes distressed if separated from its K/V cache. Invariably chokes your PCIe lanes to death as a survival mechanism. Nature is beautiful.
|