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---
base_model: Magpie-Align/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05
datasets:
- princeton-nlp/llama3-ultrafeedback-armorm
language:
- en
library_name: transformers
license: llama3.1
quantized_by: mradermacher
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
---
## About
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static quants of https://huggingface.co./Magpie-Align/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05
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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
## 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/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05-GGUF/resolve/main/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05.IQ3_S.gguf) | IQ3_S | 3.8 | beats Q3_K* |
| [GGUF](https://huggingface.co./mradermacher/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05-GGUF/resolve/main/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05.IQ3_M.gguf) | IQ3_M | 3.9 | |
| [GGUF](https://huggingface.co./mradermacher/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05-GGUF/resolve/main/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
| [GGUF](https://huggingface.co./mradermacher/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05-GGUF/resolve/main/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |
| [GGUF](https://huggingface.co./mradermacher/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05-GGUF/resolve/main/Llama-3.1-8B-Magpie-SFT-950K-UltraDPO-05.f16.gguf) | f16 | 16.2 | 16 bpw, overkill |
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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