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metadata
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

weighted/imatrix quants of https://huggingface.co/ajibawa-2023/Code-Llama-3-8B

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 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 i1-Q2_K 3.3 IQ3_XXS probably better
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):

image.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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.