--- 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](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): ![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.