ModelHub XC 2c22f8764e 初始化项目,由ModelHub XC社区提供模型
Model: mradermacher/meta-llama-Meta-Llama-3-8B-Instruct-fine-tune-english-LISA-GGUF
Source: Original Platform
2026-04-10 11:25:55 +08:00

base_model, language, library_name, quantized_by, tags
base_model language library_name quantized_by tags
JiaweiGuo123/meta-llama-Meta-Llama-3-8B-Instruct-fine-tune-english-LISA
en
transformers mradermacher

About

static quants of https://huggingface.co/JiaweiGuo123/meta-llama-Meta-Llama-3-8B-Instruct-fine-tune-english-LISA

weighted/imatrix quants are available at https://huggingface.co/mradermacher/meta-llama-Meta-Llama-3-8B-Instruct-fine-tune-english-LISA-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.

Description
Model synced from source: mradermacher/meta-llama-Meta-Llama-3-8B-Instruct-fine-tune-english-LISA-GGUF
Readme 58 KiB