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---
base_model: sophosympatheia/Midnight-Rose-103B-v2.0.3
language:
- en
library_name: transformers
license: llama2
quantized_by: mradermacher
---
## About
static quantize of https://huggingface.co/sophosympatheia/Midnight-Rose-103B-v2.0.3/
weighted/imatrix wuants can be found at https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-i1-GGUF
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-i1-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/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q2_K.gguf) | Q2_K | 38.3 | |
| [GGUF](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.IQ3_XS.gguf) | IQ3_XS | 42.3 | |
| [GGUF](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q3_K_XS.gguf) | Q3_K_XS | 42.4 | |
| [GGUF](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.IQ3_S.gguf) | IQ3_S | 44.7 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q3_K_S.gguf) | Q3_K_S | 44.9 | |
| [GGUF](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.IQ3_M.gguf) | IQ3_M | 46.2 | |
| [PART 1](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q3_K_M.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q3_K_M.gguf.split-ab) | Q3_K_M | 50.0 | lower quality |
| [PART 1](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q3_K_L.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q3_K_L.gguf.split-ab) | Q3_K_L | 54.5 | |
| [PART 1](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.IQ4_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.IQ4_XS.gguf.part2of2) | IQ4_XS | 55.7 | |
| [PART 1](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q4_K_S.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q4_K_S.gguf.split-ab) | Q4_K_S | 59.0 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q4_K_M.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q4_K_M.gguf.split-ab) | Q4_K_M | 62.3 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q5_K_S.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q5_K_S.gguf.split-ab) | Q5_K_S | 71.4 | |
| [PART 1](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q5_K_M.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q5_K_M.gguf.split-ab) | Q5_K_M | 73.3 | |
| [PART 1](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q6_K.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q6_K.gguf.split-ab) | Q6_K | 85.1 | very good quality |
| [PART 1](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q8_0.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q8_0.gguf.split-ab) [PART 3](https://huggingface.co/mradermacher/Midnight-Rose-103B-v2.0.3-GGUF/resolve/main/Midnight-Rose-103B-v2.0.3.Q8_0.gguf.split-ac) | Q8_0 | 110.0 | 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
## 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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