---
base_model: elinas/Llama-3-8B-Ultra-Instruct
language:
- en
library_name: transformers
license: llama3
quantized_by: mradermacher
tags:
- mergekit
- merge
---
## About

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weighted/imatrix quants of https://huggingface.co/elinas/Llama-3-8B-Ultra-Instruct

You should use `--override-kv tokenizer.ggml.pre=str:llama3` and a current llama.cpp version to work around a bug in llama.cpp that made these quants. (see https://old.reddit.com/r/LocalLLaMA/comments/1cg0z1i/bpe_pretokenization_support_is_now_merged_llamacpp/?share_id=5dBFB9x0cOJi8vbr-Murh)

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static quants are available at https://huggingface.co/mradermacher/Llama-3-8B-Ultra-Instruct-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/Llama-3-8B-Ultra-Instruct-i1-GGUF/resolve/main/Llama-3-8B-Ultra-Instruct.i1-IQ2_M.gguf) | i1-IQ2_M | 3.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Llama-3-8B-Ultra-Instruct-i1-GGUF/resolve/main/Llama-3-8B-Ultra-Instruct.i1-Q2_K.gguf) | i1-Q2_K | 3.3 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/Llama-3-8B-Ultra-Instruct-i1-GGUF/resolve/main/Llama-3-8B-Ultra-Instruct.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.4 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Llama-3-8B-Ultra-Instruct-i1-GGUF/resolve/main/Llama-3-8B-Ultra-Instruct.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.1 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/Llama-3-8B-Ultra-Instruct-i1-GGUF/resolve/main/Llama-3-8B-Ultra-Instruct.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.8 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/Llama-3-8B-Ultra-Instruct-i1-GGUF/resolve/main/Llama-3-8B-Ultra-Instruct.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.0 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Llama-3-8B-Ultra-Instruct-i1-GGUF/resolve/main/Llama-3-8B-Ultra-Instruct.i1-Q6_K.gguf) | i1-Q6_K | 6.7 | 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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