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Replete-Coder-Llama3-8B-GGUF

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unsloth
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metadata
base_model: Replete-AI/Replete-Coder-Llama3-8B
datasets:
  - Replete-AI/code_bagel_hermes-2.5
  - Replete-AI/code_bagel
  - Replete-AI/OpenHermes-2.5-Uncensored
  - teknium/OpenHermes-2.5
  - layoric/tiny-codes-alpaca
  - glaiveai/glaive-code-assistant-v3
  - ajibawa-2023/Code-290k-ShareGPT
  - TIGER-Lab/MathInstruct
  - chargoddard/commitpack-ft-instruct-rated
  - iamturun/code_instructions_120k_alpaca
  - ise-uiuc/Magicoder-Evol-Instruct-110K
  - cognitivecomputations/dolphin-coder
  - nickrosh/Evol-Instruct-Code-80k-v1
  - coseal/CodeUltraFeedback_binarized
  - glaiveai/glaive-function-calling-v2
  - CyberNative/Code_Vulnerability_Security_DPO
  - jondurbin/airoboros-2.2
  - camel-ai
  - lmsys/lmsys-chat-1m
  - CollectiveCognition/chats-data-2023-09-22
  - CoT-Alpaca-GPT4
  - WizardLM/WizardLM_evol_instruct_70k
  - WizardLM/WizardLM_evol_instruct_V2_196k
  - teknium/GPT4-LLM-Cleaned
  - GPTeacher
  - OpenGPT
  - meta-math/MetaMathQA
  - Open-Orca/SlimOrca
  - garage-bAInd/Open-Platypus
  - anon8231489123/ShareGPT_Vicuna_unfiltered
  - Unnatural-Instructions-GPT4
language:
  - en
library_name: transformers
license: other
license_link: https://llama.meta.com/llama3/license/
license_name: llama-3
quantized_by: mradermacher
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - llama

About

static quants of https://huggingface.co/Replete-AI/Replete-Coder-Llama3-8B

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Replete-Coder-Llama3-8B-i1-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 Q2_K 3.3
GGUF IQ3_XS 3.6
GGUF Q3_K_S 3.8
GGUF IQ3_S 3.8 beats Q3_K*
GGUF IQ3_M 3.9
GGUF Q3_K_M 4.1 lower quality
GGUF Q3_K_L 4.4
GGUF IQ4_XS 4.6
GGUF Q4_K_S 4.8 fast, recommended
GGUF Q4_K_M 5.0 fast, recommended
GGUF Q5_K_S 5.7
GGUF Q5_K_M 5.8
GGUF Q6_K 6.7 very good quality
GGUF Q8_0 8.6 fast, best quality
GGUF f16 16.2 16 bpw, overkill

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.