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---
license: apache-2.0
base_model_relation: quantized
quantized_by: Quant-Cartel
base_model: rAIfle/SorcererLM-8x22b-bf16
pipeline_tag: text-generation
tags:
- chat
- iMat
- GGUF
---
```
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d888 888b 8888 8888 ,"Y88b 888 8e d88
C8888 8888D 8888 8888 "8" 888 888 88b d88888
Y888 888P Y888 888P ,ee 888 888 888 888
"88 88" "88 88" "88 888 888 888 888
b
8b,
e88'Y88 d8 888
d888 'Y ,"Y88b 888,8, d88 ,e e, 888
C8888 "8" 888 888 " d88888 d88 88b 888
Y888 ,d ,ee 888 888 888 888 , 888
"88,d88 "88 888 888 888 "YeeP" 888
PROUDLY PRESENTS
```
# SorcererLM-8x22b-iMat-GGUF
Quantized with love from fp16 using the `alpha=32` version.
Original model author: [rAIfle](https://huggingface.co/rAIfle/)
* Importance Matrix calculated using [groups_merged.txt](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384) in 105 chunks, n_ctx=512, and fp16 precision weights
Original model README [here](https://huggingface.co/rAIfle/SorcererLM-8x22b-bf16) and below:
# SorcererLM-8x22b-bf16
<img src="https://files.catbox.moe/1kohx8.png" width="400"/>
<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/6569a4ed2419be6072890cf8/L_uGojVkNUsK6QHvWgs9o.mpga"></audio>
Oh boy, here we go. Low-rank (`r=16, alpha=32`) 16bit-LoRA on top of [WizardLM-2-8x22B](https://huggingface.co/alpindale/WizardLM-2-8x22B), trained on 2 epochs of (cleaned & deduped) c2-logs. As far as I can tell, this is an upgrade from `WizardLM-2-8x22B` for RP purposes.
Alongside this ready-to-use release I'm also releasing the LoRA itself as well as the earlier `epoch1`-checkpoint of the LoRA.
## Why A LoRA?
The choice was fully intentional. I briefly considered a FFT but for this particular use-case a LoRA seemed a better fit. `WizardLM-2-8x22B` is smart by itself but its used vocabulary leaves much to be desired when it comes to RP. By training a low-rank LoRA on top of it to teach it some of Claude's writing style, we remedy that.
## Prompting
- Use the templates in [Quant-Cartel/Recommended-Settings](https://huggingface.co/Quant-Cartel/Recommended-Settings) under the `SorcererLM`-folder.
- Or Vicuna 1.1 and a sane context template. It's somewhat sensitive to samplers, I'd recommend Temperature 1, MinP 0.05 and a dash of DRY but YMMV. Shorter prompts seem to work better, too.
## Quantized Versions
- [iMat GGUFs](https://huggingface.co/Quant-Cartel/SorcererLM-8x22b-iMat-GGUF)
- [longcal exl2s](https://huggingface.co/Quant-Cartel/SorcererLM-8x22b-exl2-longcal)
## Acknowledgments
The main shoutout I want to make is to my [Cartel](https://huggingface.co/Quant-Cartel) bros, [Envoid](https://huggingface.co/Envoid) and particularly [I^2](https://huggingface.co/InferenceIllusionist), for being amazing. I count this as a team effort, so they deserve kudos too if you like this.
## Training
Trained using [qlora-pipe](https://github.com/tdrussell/qlora-pipe). Configs included in the `train`-subfolder.
## Safety
... n/a |