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---
exported_from: ValiantLabs/Llama3-70B-ShiningValiant2
language:
- en
library_name: transformers
license: other
license_link: https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct/blob/main/LICENSE
license_name: llama3
model_type: llama
quantized_by: mradermacher
tags:
- shining-valiant
- shining-valiant-2
- valiant
- valiant-labs
- llama
- llama-3
- llama-3-instruct
- llama-3-instruct-70b
- 70b
- conversational
- chat
- instruct
---
## About
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static quants of https://huggingface.co/ValiantLabs/Llama3-70B-ShiningValiant2
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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 |
|:-----|:-----|--------:|:------|
| [PART 1](https://huggingface.co/mradermacher/Llama3-70B-ShiningValiant2-GGUF/resolve/main/Llama3-70B-ShiningValiant2.Q8_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Llama3-70B-ShiningValiant2-GGUF/resolve/main/Llama3-70B-ShiningValiant2.Q8_0.gguf.part2of2) | Q8_0 | 75.1 | 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
## 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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