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---
base_model: ibivibiv/hydra-moe-120b
language:
- en
library_name: transformers
license: apache-2.0
no_imarix: https://github.com/ggerganov/llama.cpp/issues/6597
quantized_by: mradermacher
tags:
- moe
- moerge
---
## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
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<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/ibivibiv/hydra-moe-120b
**No more quants will be forthcoming, as llama.cpp segfaults.**
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/hydra-moe-120b-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/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-IQ2_M.gguf) | i1-IQ2_M | 37.3 | |
| [GGUF](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q2_K.gguf) | i1-Q2_K | 41.6 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 43.8 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q3_K_S.gguf) | i1-Q3_K_S | 49.1 | IQ3_XS probably better |
| [PART 1](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q3_K_M.gguf.part2of2) | i1-Q3_K_M | 54.5 | IQ3_S probably better |
| [PART 1](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q3_K_L.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q3_K_L.gguf.part2of2) | i1-Q3_K_L | 59.1 | IQ3_M probably better |
| [PART 1](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-IQ4_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-IQ4_XS.gguf.part2of2) | i1-IQ4_XS | 60.7 | |
| [PART 1](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q4_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q4_0.gguf.part2of2) | i1-Q4_0 | 64.4 | fast, low quality |
| [PART 1](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q4_K_S.gguf.part2of2) | i1-Q4_K_S | 64.7 | optimal size/speed/quality |
| [PART 1](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q4_K_M.gguf.part2of2) | i1-Q4_K_M | 68.8 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q5_K_S.gguf.part2of2) | i1-Q5_K_S | 78.3 | |
| [PART 1](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q5_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q5_K_M.gguf.part2of2) | i1-Q5_K_M | 80.7 | |
| [PART 1](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/hydra-moe-120b-i1-GGUF/resolve/main/hydra-moe-120b.i1-Q6_K.gguf.part2of2) | i1-Q6_K | 93.3 | practically like static Q6_K |
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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