---
base_model: ludis/tsukasa-120b-qlora
datasets:
- PygmalionAI/PIPPA
- lemonilia/LimaRP
language:
- en
library_name: transformers
no_imatrix: 'GGML_ASSERT: llama.cpp/ggml-quants.c:10645: grid_index >= 0'
quantized_by: mradermacher
---
## About

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weighted/imatrix quants of https://huggingface.co/ludis/tsukasa-120b-qlora

**No more quants incoming, as llmama.cpp crashes when trying to generate them.**

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static quants are available at https://huggingface.co/mradermacher/tsukasa-120b-qlora-GGUF
## 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 |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q2_K.gguf) | i1-Q2_K | 43.3 | IQ3_XXS probably better |
| [PART 1](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q3_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q3_K_S.gguf.part2of2) | i1-Q3_K_S | 50.8 | IQ3_XS probably better |
| [PART 1](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q3_K_M.gguf.part2of2) | i1-Q3_K_M | 56.7 | IQ3_S probably better |
| [PART 1](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q3_K_L.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q3_K_L.gguf.part2of2) | i1-Q3_K_L | 61.8 | IQ3_M probably better |
| [PART 1](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q4_K_S.gguf.part2of2) | i1-Q4_K_S | 66.9 | optimal size/speed/quality |
| [PART 1](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q4_K_M.gguf.part2of2) | i1-Q4_K_M | 70.7 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q5_K_S.gguf.part2of2) | i1-Q5_K_S | 81.1 |  |
| [PART 1](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q6_K.gguf.part2of2) | i1-Q6_K | 96.7 | practically like static Q6_K |
| [PART 1](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q8_0.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q8_0.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/tsukasa-120b-qlora-i1-GGUF/resolve/main/tsukasa-120b-qlora.i1-Q8_0.gguf.part3of3) | i1-Q8_0 | 125.2 | fast, best quality |

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

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