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---
base_model: ajibawa-2023/Code-Llama-3-8B
datasets:
- ajibawa-2023/Code-290k-ShareGPT
- m-a-p/CodeFeedback-Filtered-Instruction
- m-a-p/Code-Feedback
- microsoft/orca-math-word-problems-200k
language:
- en
library_name: transformers
license: llama3
quantized_by: mradermacher
tags:
- code
- Python
- Cpp
- PHP
- JS
- Java
- Rust
- Ruby
- SQL
- MySql
- R
- Julia
---
## About
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weighted/imatrix quants of https://huggingface.co/ajibawa-2023/Code-Llama-3-8B
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static quants are available at https://huggingface.co/mradermacher/Code-Llama-3-8B-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/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q2_K.gguf) | i1-Q2_K | 3.3 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/Code-Llama-3-8B-i1-GGUF/resolve/main/Code-Llama-3-8B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.8 | optimal size/speed/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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