Downloads · 30 days
595
21% of all-time downloads
LucianoM39/flushnet-local-llama-3.1-8b-q4km-layers
flushnet-local-llama-3.1-8b-q4km-layers is a machine learning model from LucianoM39. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for llama.cpp. The card lists the license as llama3.1.
Downloads · 30 days
595
21% of all-time downloads
All-time downloads
2.8K
Public
Repo size
5.2 GB
Likes
0
Public
Click a slice to open those files.
.gguf5.2 GB · 100%
From the Hugging Face model README
Built with Llama.
This repository contains a Mesh-LLM layer package derived from a locally provisioned Meta Llama 3.1 8B Instruct Q4_K_M GGUF model. It is intended for Mesh-LLM-compatible runtimes that support model-package.json and per-layer GGUF artifacts.
model-package.json — package manifestshared/ — metadata, embeddings, and output tensorslayers/ — 32 per-layer GGUF artifactsThis is not a conventional single-file GGUF download. Use it with a compatible Mesh-LLM package-aware runtime. The original monolithic GGUF source file is not included in this repository.
The package was assembled locally from a Meta Llama 3.1 8B Instruct Q4_K_M GGUF source. The original acquisition location was not preserved in the local package metadata. The manifest retains artifact hashes for the published package.
This repository distributes a quantized derivative of Meta Llama 3.1. Use, redistribution, and any derived distribution are governed by the Meta Llama 3.1 Community License Agreement and the Meta Llama Acceptable Use Policy. A copy of the community license is included in LICENSE.
By downloading or using these files, you are responsible for complying with the applicable Llama license and acceptable use policy. This repository is provided without warranty.
The package was prepared for AI-MAX / Mesh-LLM experiments. Verify runtime compatibility and available memory before deployment. Remote CPU-backed storage is not native GPU memory; required data must be staged into local Metal or GPU memory for inference.