ModelHub XC 2d6bec8f7e 初始化项目,由ModelHub XC社区提供模型
Model: mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF
Source: Original Platform
2026-06-06 17:21:16 +08:00

base_model, datasets, language, library_name, license, license_link, license_name, quantized_by, tags
base_model datasets language library_name license license_link license_name quantized_by tags
Replete-AI/Llama3-8B-Instruct-Replete-Adapted
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
en
transformers other https://llama.meta.com/llama3/license/ llama-3 mradermacher
text-generation-inference
transformers
unsloth
llama

About

weighted/imatrix quants of https://huggingface.co/Replete-AI/Llama3-8B-Instruct-Replete-Adapted

static quants are available at https://huggingface.co/mradermacher/Llama3-8B-Instruct-Replete-Adapted-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-IQ1_S 2.1 for the desperate
GGUF i1-IQ1_M 2.3 mostly desperate
GGUF i1-IQ2_XXS 2.5
GGUF i1-IQ2_XS 2.7
GGUF i1-IQ2_S 2.9
GGUF i1-IQ2_M 3.0
GGUF i1-Q2_K 3.3 IQ3_XXS probably better
GGUF i1-IQ3_XXS 3.4 lower quality
GGUF i1-IQ3_XS 3.6
GGUF i1-Q3_K_S 3.8 IQ3_XS probably better
GGUF i1-IQ3_S 3.8 beats Q3_K*
GGUF i1-IQ3_M 3.9
GGUF i1-Q3_K_M 4.1 IQ3_S probably better
GGUF i1-Q3_K_L 4.4 IQ3_M probably better
GGUF i1-IQ4_XS 4.5
GGUF i1-Q4_0 4.8 fast, low quality
GGUF i1-Q4_K_S 4.8 optimal size/speed/quality
GGUF i1-Q4_K_M 5.0 fast, recommended
GGUF i1-Q5_K_S 5.7
GGUF i1-Q5_K_M 5.8
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

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

Description
Model synced from source: mradermacher/Llama3-8B-Instruct-Replete-Adapted-i1-GGUF
Readme 29 KiB